Title of Invention	A RECEPTION METHOD AND SYSTEM FOR COMMUNICATION OVER FREQUENCY-SELECTIVE CHANNELS TO PROCESS RECEIVED DATA
Abstract	The invention relates to a receiving method for communications on a frequency selective channel having a large number of transmitting and receiving antennas which is characterised in that it makes it possible to process data which is successively modulated, spread and processed prior to the transmission thereof and is received by the receiving antennas. For this purpose, the inventive method consists in carrying out: a first linear filtering (202, 202'), a first interference subtraction (201) which uses a pre-regenerated inter-antenna (MAI) and intersymbol (ISI) interference estimate, a second linear filtering (205, 205'), a second interference subtraction (201) which uses a pre-regenerated interuser (MUI) interference estimate and a processing which is based on the received data and generates MAI+ISI and MUI interference estimates from the thus filtered data. A receiving system for carrying out said method and a transmission system comprising said receiving system are also disclosed.

Title of Invention

A RECEPTION METHOD AND SYSTEM FOR COMMUNICATION OVER FREQUENCY-SELECTIVE CHANNELS TO PROCESS RECEIVED DATA

Abstract

The invention relates to a receiving method for communications on a frequency selective channel having a large number of transmitting and receiving antennas which is characterised in that it makes it possible to process data which is successively modulated, spread and processed prior to the transmission thereof and is received by the receiving antennas. For this purpose, the inventive method consists in carrying out: a first linear filtering (202, 202'), a first interference subtraction (201) which uses a pre-regenerated inter-antenna (MAI) and intersymbol (ISI) interference estimate, a second linear filtering (205, 205'), a second interference subtraction (201) which uses a pre-regenerated interuser (MUI) interference estimate and a processing which is based on the received data and generates MAI+ISI and MUI interference estimates from the thus filtered data. A receiving system for carrying out said method and a transmission system comprising said receiving system are also disclosed.

Full Text	F0RM2 THE PATENTS ACT, 1970 (39 of 1970) & THE PATENTS RULES, 2003 COMPLETE SPECIFICATION (See section 10, rule 13) "DISJOINT ITERATIVE CHIP EQUALISATION AND MULTI-USER DETECTION FOR CDMA COMMUNICATION SYSTEMS ON A MIMO CHANNEL" FRANCE TELECOM French Limited Company of 6 Place d'Alleray F-75015, Paris, France The following specification particularly describes the invention and the manner in which it is to be performed. DISJOINT ITERATIVE CHIP EQUALISATION AND MULTI-USER DETECTION FOR CDMA COMMUNICATION SYSTEMS ON A MIMO CHANNEL 5 GENERAL TECHNICAL FIELD The present invention relates to the field of digital communications. It concerns how to decode efficiently digital data transmitted on a frequency-selective MIMO channel at the same time as optimizing the 10 performance1complexity trade-off. Figure 1 shows an overall method of transmission on a frequency-selective MIMO channel 300 between a sender 100 with T send antennas, delivering signals x[n] at the time n, and a receiver 200 with R receive antennas, receiving signals 15 y[n] at the time n. GENERAL DESCRIPTION OF THE PRIOR ART Any communications system managing the access of multiple users to the same channel by allocating specific 20 spreading codes (CDMA) is limited in capacity by multiuser interference (MUI) between users. In the context of the present invention, transmission is envisaged on a channel liable to generate other kinds of interference such as spatial multi-antenna interference (MAI) caused 25 by multiple send antennas and intersymbol interference (ISI) caused by the frequency selectivity of the channel. On reception, these various kinds of interference are cumulative and make recovering the useful information difficult. 30 Pioneering work carried out by S. Verdu in the 1980s clearly demonstrated the benefit of exploiting the structural properties of multi-user interference (MUI), multi-antenna interference (MAI) and intersymbol interference (ISI) to improve performance for a fixed 35 load (the number of users per chip) or to improve the load for fixed performance. 73 Many types of linear detectors have been studied, capable of supporting a greater or lesser load, which load may be evaluated analytically under asymptotic conditions. Without recourse to iterative techniques, 5 the performance of these detectors falls far short of the performance of a maximum likelihood (ML) detector (for a system with or without coding). The class of non-linear LIC-ID detectors based on linear iterative cancellation of the interference thus 10 offers an excellent trade-off between performance and complexity. LIC-ID detectors use the following functions: linear filtering, weig[n]Ted regeneration of interference (regardless of its nature), subtraction of the regenerated interference from the received signal. 15 They deliver decisions on the sent modulated data (or symbols) with a reliability that increases in monotonous fashion with each new attempt. LIC-ID detectors which are intended to eliminate ISI (at block level) asymptotically achieve the performance of an optimum ML 20 detector with a computation complexity similar to that of a linear equalizer. LIC-ID detectors intended to combat MUI approximate the performance of the optimum ML detector with a computation complexity comparable to that of a simple linear detector. 25 A remarkable feature of LIC-ID detectors is that they can easily be combined with hard or weig[n]Ted decisions delivered by the channel decoder, thus effecting separate and iterative detection and decoding of the data. 30 For CDMA systems that are overloaded (by hypothesis by MUI) transmitting on frequency-selective MIMO channels, the level of interference is such that using LIC-ID receivers proves essential. If an iterative strategy is selected, the complexity of the receivers can 35 be reduced, and rendered reasonable, only by simplifying the iterative processing as much as possible. LIC-ID detectors are treated separately for ISI and for MUI in reference [1] (see below) and in the case of ISI+MUI in reference [2] (see below). [1] A.M. Chan, G.W. Wornell, "A New Class of Efficient 5 Block-Iterative Interference Cancellation Techniques for Digital Communication Receivers", IEEE J. VLSI Signal Processing (Special Issue on Signal Processing for Wireless Communication Systems), vol. 30, pp. 197-215, Jan.-Mar. 2002. 10 [2] W. Wang, V.H. Poor, "Iterative (Turbo) Soft Interference Cancellation and Decoding for Coded CDMA", IEEE Trans. Commun., vol. COM-47, no. 9, pp. 2356-2374, Sept. 1999. 15 Their generalization to MUI+MAI+ISI still constitutes an open subject of research, in particular because of the complexity of the processing to be effected, implying computations on particularly large 20 matrices. If a hypothesis of orthogonality exists between the various users on sending, one tempting approach is to re-establish orthogonality at the chip level before any 25 attempt at multi-user detection. Optimum multi-user detection then amounts to a bank of filters matched to each user. This approach, developed in document [3] (see below) for a non-overloaded CDMA communications model transmitting on a frequency-selective SISO channel, 30 proves to be the optimum when aperiodic spreading is considered, for example. [3] M. Lenardi, D.T. Slock, "A Rake Receiver with Intracell Interference Cancellation for PS-CDMA 35 Synchronous Downlink with Orthogonal Codes," IEEE VTC, pp. 430-434, 2000. 75 The present invention goes beyond the framework of the above reference by considering an overloaded CDMA communications model transmitting on a frequency-selective MIMO channel. 5 SUMMARY OF THE INVENTION A first aspect of the invention proposes a receiving method according to any one of claims 1 to 21. A second aspect of the invention proposes a 10 transmission system according to claim 22. A third aspect of the invention proposes a receiving method according to any one of claims 23 to 33. An object of the present invention is to propose a receiver for "multicode" CDMA transmission (K > T) and1or 15 overloaded CDMA transmission (K potential users or streams, spreading factor N 20 and a perfect knowledge of the CSI at the receiver. The receiver is based on a combination of simple mechanisms and techniques to obtain the best possible quality of service at fixed spectral efficiency and signal-to-noise ratio (SNR) or the best possible usable bit rate at fixed 25 quality of service, band and SNR. To this end, the invention proposes a device comprising: • Means for guaranteeing temporal decorrelation of samples of noise affecting the chips when the multiple 30 access model with K potential users is reformed on reception assuming the absence of MAI+ISI, said means comprising chip interleaving before transmission over the MIMO channel or aperiodic spreading. Note that although chip interleaving is not necessary for internal linear 35 aperiodic coding, it remains an option. The invention proposes an equalization and iterative decoding device including a data detector receiving the data coming from the various send antennas comprising: • first linear filtering processing for each send 5 antenna the MAI+ISI interference and generating statistics on the chips sent using the spatial diversity offered by the R receive antennas; • means for subtracting, before or after any linear filtering associated with each send antenna, from the 10 received signal the MAI+ISI interference regenerated for that antenna from the available estimates of the sent modulated data (or symbolic data); • means for reordering the equalized chips into a multiple access system with K potential users in which 15 the additive noise affecting the various chips is assumed to be Gaussian white noise; • second linear filtering processing the MUI interference on the basis of the chips previously equalized and reordered and generating statistics on the 20 symbolic data sent by each of the K potential users; • means for subtracting, before or after any linear filtering for each user, from the observed signal the MUI interference regenerated for that user from available estimates of the symbolic data sent; 25 • means for processing these statistics and generating probabilistic bit information usable for external decoding; • external decoding with weig[n]Ted inputs and outputs, capable of generating probabilistic information 30 referred to as extrinsic information, pertinent for the calculation of the estimates of the sent symbolic data (in the sense of the criterion of minimizing the mean square error (MMSE)); • means for recursively concatenating the output of 35 the external decoder both with the MAI+ISI interference regenerator, and with the MUI interference regenerator. DESCRIPTION OF THE DRAWINGS Other features and advantages of the invention will emerge from the following description, which is purely illustrative and non-limiting and should be read with 5 reference to the appended drawings in which: • Figure 1 illustrates a general concept of transmission on a frequency-selective MIMO channel; • Figure 2 shows a first part of a sending process, including external channel coding of digital information, 10 interleaving, and demultiplexing into K streams (one for each potential user) ; • Figure 3 shows the second part of the Figure 2 sending process, including internal linear coding corresponding to aperiodic space-time (space-frequency) 15 spreading followed by multiplexing onto the T send antennas; • Figure 4 shows a second portion of the Figure 2 sending method, including internal linear coding corresponding to aperiodic space-time (or 20 space-frequency) spreading, multiplexing onto a single channel, interleaving at chip level, and demultiplexing to the T send antennas; • Figure 5 shows a first part of a variant of a sending method including external channel coding of 25 digital information, interleaving, first demultiplexing (space demultiplexing) into T streams followed by second demultiplexing (code demultiplexing) into U streams; • Figure 6 shows the second part of the Figure 5 sending method, including aperiodic time (or frequency) 30 spreading and independent multiplexing for each antenna, compatible with the UMTS HSDPA mode; • Figure 7 shows a second portion of the Figure 4 sending method, including aperiodic time (or frequency) spreading followed by multiplexing onto a single channel 35 and interleaving at the chip level, followed by demultiplexing to the T send antennas, compatible with the UMTS HSDPA mode; figure 8 shows a flat ergodic or block level fading equivalent channel obtained by decomposition of the frequency-selective MIMO channel into the Fourier base and routinely used as a model for multicarrier 5 modulations; Figure 9 and 10 respectively show first and second variants of the architecture of a first portio of an LIC-ID receiver of the invention, in which only the functional units necessary for understanding the 10 algorithm are indicated; Figure 9 related to a sending scheme according to Figure 2-4 and 5-7 and Figure 10 relates to the sending scheme described with reference to Figure 2-3 and 5-6; Figure 11a and 11b represent two equivalent 15 methods of implementing LIC-ID receivers for processing MAI+ISI interference, the Figure 11a implementation method representing the filtering and MaI+ISI interference regeneration parts of the first part of the overall detector shown in Figure 9 or Figure 10. 20 Figure 12 a and 12b represent receivers two equivalent methods of implementing LIC-ID receivers for processing MUI interference, the implementation method of Figure 12a representing the filtering and MUI interference regeneration parts of the first part of the overall 25 detector showm in Fiugure 9 or Figure 10; Figure 13 shows the architecture of the second part of the LIC-ID receiver according to the invention ( the first portion of the detector being represented by Figure 9 or Figure 10), in which only the functional 30 units necessary for understanding the algorithm are indicated DESCRIPTION OF PREFERRED EMBODIMENTS OF THE PRESENT INVENTION 1. General structure of the sender Reception is intimately linked to the sending mode, 5 which can be defined by a modulation1coding scheme of high spectral efficiency, and high adaptability capacity, based on the use of spread spectrum modulation and on the use of multiple send and receive antennas. The proposed solution is pertinent assuming no knowledge of the send 10 channel (no CSI) and a perfect knowledge of the receive channel (CSI). The communications model is briefly described below in order to introduce a third embodiment of the present invention. Referring to Figure 2 and Figure 5, the useful 15 digital data is collected and grouped into a message m of K0 bits constituting the send digital data source 101. In each message m, a linear external code C0 having an N0 x K0 generator matrix G0 and constructed on F2 assigns at 102 a code word v of length N0 bits defined by the 20 matrix equation: v = G0 m The external coding yield is: The length N0 of the code words is linked to the 25 various parameters of the system by the equation: N0 = K X L X q in which K designates the total number of potential users, L the length of the packets (in symbol times) and q the number of bits per modulation symbol. The code may 3 0 be of any type, for example a convolutional code, a turbocode, an LDPC code, etc. In a multiple access type configuration, the message m consists in a plurality of multiplexed messages from different sources. Coding is effected independently on each component message. The 35 code word v results from the concatenation 103 of the various code words produced. The code word v is sent to an interleaver 104 operating at the bit level and, where appropriate, having a particular structure. In a multiple access type configuration, the interleaving acts piece by piece on 5 the various code words placed one after the other. The output of this interleaver is broken up into KL sets of g bits called integers. The stream of integers is demultiplexed 105 onto K separate channels, where K may be chosen arbitrarily to 10 be strictly greater than the number T of send antennas. The output from this operation is a K x L integer matrix D. The L columns d[n] n = 0, ..., L-l of this matrix D have the following structure: d[n] = [d1[n]T d2[n]T ... dK[n]T]T F2 15 in which the component integers dk[n] k = 1, ..., K are themselves structured as follows: Referring to Figure 3, 4, 6, or 7, the integers dk [n] of the matrix D are then individually modulated 107 via a 20 modulation table :F1 to yield modulated data, or more precisely complex symbols sk[n] of a constellation with Q = 2q elements. This transforms the integer matrix D into a K x L complex matrix S the L columns s[n] n = 0, ..., L-l whereof are structured as follows: 25 s[n]D11(d[w]) = [,[n] s2[n] ... sK[n]J e3K It is useful to specify the following inverse relationships: 11-'(sH)DdH frl(sk[n])Udk[n] tf (sk[n])U dkJ[n] This is followed by internal linear coding (or spreading) 30 of the data. There are several options as to the definition of the generator matrix W of the internal linear coding (more precisely: generator matrix of the internal linear coding on the body of the complexes) that may impact on the structure of the sender and on the 35 characteristics of the linear front-ends on reception. Periodic spreading (or internal linear coding) where W is used again in each symbol time. To guarantee temporal decorrelation of the samples of noise affecting the chips when the multiple access system is reformed 5 after equalization, chip interleaving must be applied before transmission over the MIMO channel; • Aperiodic spreading (or internal linear coding) where Wn depends explicitly on the symbol time. Aperiodic spreading guarantees temporal decorrelation of the 10 samples of noise affecting the chips when the multiple access system is reformed after equalization. Chip interleaving is no longer necessary but remains an option. Moreover, the spreading may be space-time (or 15 space-frequency) spreading or only time (or frequency) spreading if it is effected independently for each antenna. 1.1 Space-time (or space-frequency) spreading (or 20 internal linear coding) under .overload conditions Referring to Figure 3 or Figure 4, it is assumed here that aperiodic space-time (or space-frequency) spreading is effected. The space-time (or space-frequency) spreading is 25 effected for each matrix S by means of an N x K internal coding matrix Wn, which is denoted W in the periodic context), where: N = TxSF SFGD This generator matrix is also called a spreading 30 matrix. For example, this matrix may be considered to be constructed from N orthogonal spreading codes with spreading factor N. This internal linear coding therefore corresponds, in this case, to space-time (space-frequency) spreading with spreading factor N. The 35 internal coding yield (or load) of the system is the ratio: The multiplication at 108 of the symbol vectors s[n] by the generator matrix Wn produces a vector: 5 zHDW„s[n] = [z,[n] z2[n] ... z,[n]]TeD" The relationship may also be written at the matrix level: 10 1.1.1 Spreading followed by chip interleaving Chip interleaving is necessary if the spreading is periodic (W = Wn) in order to be able (afterwards) to implement reception in accordance with the invention. Referring to Figure 4, the chip vectors z[n] 15 n = 0,...,Z-1 are multiplexed at 109 into a single stream of chips. The chip stream then drives a chip interleaver 110, the output whereof is demultiplexed at 111 into T separate chip, streams (one for each send antenna). The effect of this operation is to transform the NxL chip 20 matrix Z: Z = [z[0] z[l] ••• z[Z-l]]eDWxL into a TxLSF chip matrix X: X = [x[0] x[l] - x[LSF-1]]eUTxLS' the columns x[1] 1 = 0,---,ZS'F -1 whereof constitute the inputs 25 of the MIMO channel: x[1] = [,[1] x2[l] - xT[l]]J^T 1.1.2 Spreading not followed by chip interleaving Referring to Figure 3, the chip vectors z[n] 30 n = 0,...,L-1 are demultiplexed into T separate chip streams (111, one for each send antenna). The effect of this operation is to transform the NxL chip matrix Z: Z = [z[0] z[l] - z[L-l]]eUNL into a TXLSF chip matrix X: IS 13 X = [x[0] x[l] ••• x[LSF-1]]Є‮ TxLSF the columns x[1] I = 0,---,LSF-1 whereof constitute the inputs of the MIMO channel: x[1] = [x,[1] x2[l] ... xT[l]TЄ‮T 5 1.2 Time (or frequency) spreading (internal linear coding) In this variant of the invention, shown in Figure 6 or Figure 7, compatible with the HSDPA mode of the UMTS 10 standard, there are SF orthogonal codes of length SF . The parameter N is always a multiple of T: N = TxSF SFЄ‮ The SF available codes are re-used at each send antenna (this is the code re-use principle). The 15 spreading, effected independently for each antenna, is periodic or aperiodic time (or frequency) spreading (W = Wn in the periodic context). This imposes that K be also a multiple of T: K=TxU UeU 20 This condition, which is not limiting on the invention, yields a new expression for the internal coding yield (load): The generator matrix Wn has a block diagonal structure: "w(1) o n NxK ;□ W(2) 25 W = (D w„ the block W„of the generator matrix being associated with the antenna t with dimension SF X U . Referring to Figure 5, the integer vector d[n] 30 (demultiplexed at 105, after being coded at 102 and interleaved at 104) sent at the time n has the following particular structure: V51h d[n] = [d(1)[n]T d(2)[n]T ... d{T)[n]TЄ F2qk in which the symbol vectors d(l)[n]t = l,...,T are themselves defined as follows: d(1)[n] = [d1(t)[n]T d1(t)[n]T … d(T)[n]T]T ЄF2qk 5 Referring to Figure 5, the modulation 107 of this multiplexed data d[n] yields a modulated data (or symbols) vector sent at the time n having the following particular structure: s[n] = [s(1)[n]T s{2)[n]T ... s(T)[n]T… [n]T]TЄ‮k 10 in which the symbol vectors s(1)[n] t = l,...,T are themselves defined as follows: s(1)[n]= [s1(1)[n]s2(1)[n]TЄ‮U The multiplication 108 of the symbol vector s[n] by the generator matrix Wn produces the vector: 15 z[n]‮Wns[n] which also has a particular structure: z(1)[n]‮WnS[n]T z(2)[n]T ... z(T)[n]T]TЄ‮N in which the chip vectors z(1)[n] t = 1,...,T are themselves defined as follows: 20 z(1)[n]‮Wn(t)s(t)[n]= [z1(t)[n] z2(t)[n] ... z(t)sF [n]]TЄ‮ 1.2.1 Spreading followed by chip interleaving Chip interleaving is necessary if the spreading is periodic (W = Wn) in order to be able (afterwards) to 25 implement reception in accordance with the invention. Referring to Figure 7, the chip vectors z[n] n = 0,...,L-l are multiplexed at 109 into a single stream of chips. The chip stream then drives a chip interleaver 110, the output whereof is demultiplexed at 111 into T 30 separate chip streams (one for each send antenna). The effect of this operation is to transform the NxL chip matrix Z: Z = [z[0] z[l] ••• z[L-l]]Є‮NxL into a TxLSF chip matrix X: X = [x[0] x[l] - x[LSF-1]]Є‮TxLSr the columns x[1] I = 0,---,LSF -1 whereof constitute the inputs of the MIMO channel: 5 x[1] = [x1[1] x2[l] ….. xT[1]]TЄ‮T 1.2.2 Spreading not followed by chip interleaving Referring to Figure 6, the chip vectors z(t) [n] are then multiplexed at 109-t onto the send antenna t. 10 It will be noted that, in this sending variant, the recovery of the spatial diversity is effected via the code G0 (at 102) and external bit interleaving (at 104). The overload capacity, which is known to increase with the length of the spreading codes, is lower. 15 The sending method fits naturally into the general class of space-time codes. The spectral efficiency of the system (in bits per use of the channel), assuming a limited band ideal Nyquist filter, is equal to: η = TXp0XqXa 20 In practice, the send shaping filter has a non-null overflow factor (roll-off) e. At the receiver, a filter matched to this send filter could be used for all the receive antennas. It is assumed that the channel estimation and timing and carrier synchronization 25 functions are implemented so that the coefficients of the impulse response of the channel are regularly spaced by an amount equal to the chip time (channel equivalent in the discrete baseband to the discrete time). This hypothesis is legitimate, the Shannon sampling theorem 30 imposing sampling at the rate {1 + Є)/ Tc which may be approximated by 1/TC when e is small. Direct generalization is possible for expressions given below for a sampling rate equal to a multiple of 1/Tc . 35 2. Channel model Transmission is effected on a frequency-selective B-block. channel with multiple inputs and multiple outputs (MIMO): H‮{H(1),H(2),...,H(B)} The channel H(b) is assumed constant over Lx chips 5 with the convention: LXSF=BXLx BЄ‮ The chip matrix X may be segmented into B separate TxLx chip matrices X(1),...,X(S) (padded on the rig[n]T and left with physical zeros or guard times if necessary), 10 each matrix X(i) seeing the channel H(A) . The extreme cases of the B-block model are as follows: B = 1 and Lx = LSF => Ls = L quasi - static model B = LSF and Lx = 1 => Ls = 1 ergodic (chip) model 15 A renumbering of the chips is applied within each block. 2.1 Convolutional channel model For any block index b, the discrete time baseband 2 0 equivalent channel model (chip timing) is used to write the receive vector y(A)[1]en" at the chip time 1 in the form: ywM=ZH where P is the constraint length of the channel (in 25 chips), x(b)[l]Є‮T is the complex vector of T chips sent at the chip time 1, where HP(b)Є‮RXT is the matrix coefficient indexed p of the impulse response of the block MIMO channel indexed b, and v(6)[1]Є‮T is the complex additive noise vector. The complex additive noise vectors v(A)[1] 3 0 are assumed to be independent and identically distributed in accordance with an R-dimensional Gaussian law of circular symmetry with zero mean and covariance matrix G2I. The P coefficients of the impulse response are RxT complex matrices, the inputs of which are 35 identically distributed independent Gaussian inputs, with zero mean and with a covariance matrix satisfying the global power normalization constraint: p-1 [P'O = 71 in the case of a system with power equally distributed between the send antennas. Given these hypotheses, the eigen values of the correlation matrices of the coefficients of the MIMO channel conform to a Wishart distribution. It is emphasized that equal distribution of the power to the send antennas is a legitimate power allocation policy in the case of an absence of knowledge of the sending channel (no CSI). 2.2 Block matrix channel model To introduce the data decoding algorithm, we must show a matrix system on the set of the type: T(b) =n()x()+vw y( where: ywn[y(A)[^-i+^-i]T y{b)[Lx-2+p-1f - y^[o]T eD (Lx+P-l)R ,()! [v{b)[Lx-1 + P-1f v{h)[Lx-2 + P-1f ... v(A)[0]T]T6D(L^-1)1? x(6)D >[I„-1]T W[LX-2]J A>>) [of s D LxT r(ft) and where FT' is the Sylvester matrix for the channel (ft) HI") H-! H (4) _ H (ft) (ft) (ft) (ft) H 0 Hl H (ft) H (ft) . r-\| (is+M)RSFxZ.Jref. H (ft) H (ft) H (ft) H (ft) H 10 2.3 Sliding window matrix channel model In practice, to reduce the dimensions, a .sliding window model is -used of length: Lw = Ll+L2+1‮ Ls The following new system is obtained: ywH = y(i)x(A)H+Y(6)[n] where: L„,R □ (L,,+P-1)T eD UvR f>[1] = [yH1 + A]T -. y(A)[1-Z2]T x(A)[1] = [x()[1 + Z1]T ••■ x(A)[1-Z2-P + lf v(A)[1] = [v(A)[1 + A]T — v(A) [1-ZjT and where Hl,is the Sylvester matrix for the channel 300 H (A) _ l"H?> H H(n) H ... H?> (A) (A) H H H (A) P-1. eQ l^RSp^Lff+M^p 20 3. Multipath MIMO channel single-carrier transmission (HSDPA) It is assumed here that the bit rate is very high and that the coherence time of the channel is long, so that LxD SF . For the HSDPA mode of the UMTS standard, the channel is quasi-static, i.e. B = 1. 4. Multipath MIMO channel multicarrier transmission (MC-CDMA) 25 The spreading (or internal linear coding) is space-frequency spreading or frequency spreading. With reference to Figure 8, it is well known to the person skilled in the art that the introduction of a send IFFT 120 and a receive FFT 220 yields (ignoring interleaving) 30 an equivalent channel that is not frequency selective (channel modeled by a circulating matrix using cyclic prefixes, then rendered diagonal in the Fourier base). Accordingly, each carrier sees a flat MIMO channel. Using the; formalism previously described, the channel after FFT may be seen as a non-selective B-block channel (P = 1). The width of the sliding window for calculating 5 the filters is lw=1. 5. General structure of the receiver 200 The iterative receiver 200 is divided into successive interference cancellation stages. A first 10 stage cancels MAI+ISI interference at chip level and attempts to re-establish orthogonality within groups of users over all the antennas. The second stage cancels MUI interference once orthogonality has been re-established within the groups of users. The two 15 stages are activated several times. Given the scale of the problem, only linear approaches based on Wiener filters (MMSE criterion) or simple (single-user) matched filters are envisaged. In both cases, a weighted version of the interference is removed before or after filtering. 20 5.1 Sent symbol MMSE estimation On any iteration i, there is assumed an a priori knowledge of the data expressed via logarithmic ratios on the bits of the sent symbols (also referred to as 25 modulated data): By convention, these ratios have the value 0 on the first iteration. Referring to Figure 9 or Figure 10, on the basis of 30 this a priori information, there can be found at 212 the matrix S' of the estimates, in the sense of the MMSE criterion, of the symbols sk[n] sent by the users k = 1,...,K at the times n = 0,...,L-l . The estimate of a symbol is expressed as follows: 35 3MQ5>xPr'\|>M=] se3 With deep space-time interleaving, the a priori probability, for a symbol may be approximated by the product of the marginal probabilities of the bits that constitute it: 5 equality being obtained for an infinite interleaving depth. To introduce the logarithmic ratio ^j[n] of the bit a priori probabilities previously defined, we may write: 10 and finally find: 5.2 Sent chip MMSE estimation 15 From estimated symbolic data vectors s"'[n], there may be created at 214 (by applying to the estimates the spreading matrix Wn used on sending) the chip vectors estimated on each iteration i: ?H = w„?'[n]=[z;H j'2[n] ... J;H]T 20 that constitutes the estimated matrix Z' This is followed by processing 215 (which may comprise multiplexing, demultiplexing, chip interleaving, block division). The processing 215 conforms to that applied on 25 sending downstream of spreading 108 (see any of Figures 3,4,6 and 7). For example, if the send processing comprises simple multiplexing to the T send antennas, as shown in Figures 3 and 6, the processing 215 comprises multiplexing onto T 30 channels (shown in Figure 10). For example, if the send processing comprises multiplexing 109 onto one channel followed by chip interleaving 110 and demultiplexing (111) to the T send 10 antennas, as shown in Figures 4 and 7, the receive processing ,215 comprises multiplexing onto one channel, chip interleaving and demultiplexing onto T channels (shown in Figure 9) 5. Following the processing 215, there are then generated (deduced from 11) the matrices Xi(1),...,Xi(B) the columns whereof are the vectors: x,(A)[1]=[x;w[1] x'{b)[i] - Jc;(A)[1]]TeDr that are used for the linear iterative cancellation of the MAI+ISI interference at 201. 15 5.3 Re-establishing orthogonality between user groups by equalization to the chip time This section considers a given block of index b that was sent by the antenna t, assuming identical processing for all of them. The invention suggests replacing optimum detection of the chips x,[l] (in the sense of the MAP enter ion) by an estimate in the sense of the 25 From ]the vector of the estimates of the chips on the iteration si:" the modifiled version is defined at 216, including a 0 at 5 position Ii^T+t , which is used to regenerate the MAI+ISI ij interference 216 for the symbol ,[/]: An estimate of MAI+ISI interference is therefore regenerated at 216 by multiplying this vector by said 10 Sylvester matrix H (its calculation is described above in section 2.2 or 2.3): The first (Wiener) filter 202 is applied to the observation vector obtained after subtraction at 201 of 15 the regenerated MAI+ISI interference: This first filter 202 minimizes the unconditional MSE on the (biased) estimate of the chip xt[l] and may easily be derived from the orthogonal projection theorem: where e, ils the vector of dimension {L^+P-YyT having a 1 at positioin LT + t and zeroes everywhere else and where: S; □ E\(x[l]-% [t])([l]-t [']) Je □ (V+^Fx(v^-Dr S^dijigj^-ai2)!,...,^-^2)!,^^-^2)!,....^-^2)!} 25 with the term (J ' ^ diagonal nnd &T evaluated using the following estimator: To satisfy the absence of bias constraint, the filter must be multiplied on the left by the correctior 30 factor: The 'Eollowing final expression for the filter is obtained: Alternatively, this filter may be replaced, completely] or from a different iteration i (i > 1), by its single'l user matched filter (SUMF) version, given by: The evaluation of the chip xt[/] then corresponds, at the outputj °f the first filter 202, to: The variance of the residual MAI+ISI interference 10 plus noise is then equal to: and may in practice be evaluated using the following estimator: 15 Other possible equalization variant: j Figuie lib shows a variant of the first filtering 202' and the regeneration of MAI+ISI interference 210', to be compared with the first filtering 202 and the i 20 regeneration of MAI+ISI interference 210 of Figure 11a (representing these two detection steps included in the \|\| Figure 9 or 10 scheme). II Referring to Figure lib, here the first filtering 202' is eilfected upstream of the first subtraction 201 of 25 the MAI+ISil interference regenerated at 210', and not downstream thereof as is the case in Figure 11a. The ilirst filter f' used and the MAI+ISI interference reconstruction matrix here denoted bi' used P . can be deduced trivially from the first filter f and the 30 MAI+ISI interference reconstruction matrix here denoted bi If previously calculated (see above description with reference to Figures 9 or 10 and 11a), from the following equation: In o"r[der then to deduce therefrom: 5.4 Equivalent Gaussian multiple access and multi-user 5 detection[model The tjwo situations distinguished on sending (i.e. space-time (space-frequency) spreading, and time (or frequency) spreading) produce 1 or T different multiple access models. 10 5.4.1 Spac'je-time (or space-frequency) send spreading Referring to Figures 9 and 10, the chip matrices X'(1),...,X'(B) are here grouped into a single matrix X , which in turn is reorganized, after processing 203, into a 15 single NxL matrix Z'; the processing 203 corresponds to the converse of the processing 215 described in section 5.2. There! is then obtained a (canonic) Gaussian equivalent.! multiple access model of the type: 20 The observed chin matrix is denoted: ~z[[0] f\|[l] - z[[L-l] Z'=[i'[0] f[l] - V[L-l]]= '2\°] '2\l] "' '2[L~l] eDM j'N[o] m ... 4[z-i]_ The riiatrix of samples of noise in time is denoted: 25 For each time n, we set: The matrdJ! of covariance of the residual MAI+ISI interference plus noise vectors. This is made diagonal either thonks to the chip de-interleaving included at 203 or the aperiodic nature of the spreading. Its diagonal 5 elements o[re deduced from the variances previously estimates To simplify subsequent processing (MMSE multi-user detection , a variance of the noise samples that is 10 constant : or the whole of the system may be assumed: The Uemporal dependency is then eliminated: "■»[«] v « v«-u,...,i, l 5.4.1.1 Periodic space-time (space-frequency) send 15 spreading As seen above, when the spreading is periodic, a chip inte;rleaver (110) is used on sending, so that the processing 203 includes chip de-interleaving (see Figure 9) 20 Variant l\|i Overloaded regime: MMSE multi-user detection Here]! the optimum detection of the symbols sk[n] (in the sense of the MAP criterion) is replaced by a non-biasei MMSE evaluation the complexity whereof is 25 polynomial in the parameters of the system and not exponential. On each iteration i, for each potential user k, tiaere is calculated at 204 a second filter g^eD" which, on the basis of an updated observation (relating to the column indexed n of the preceding model), 30 eliminates the MUI interference corrupting the symbol sk[n] and (produces an evaluation s'k[n] of the sent modulated! data (or symbols) that minimizes the mean square erjror (MSE) : subject tdf the constraint of the absence of bias. An unconditional MSE would be preferable for reasons ofo complexity: the second filter g'^. is then invariant in time for the block concerned of the particular channel 5 (i.e. calculated once and for all over the whole of the block beiisg processed) . From the vector of the estimates of the symbols at the iteration i: 10 it is possible to define at 213 the modified version, including a 0 at position k, that is used for the regeneration 213 of the MUI interference for the symbol An estimate of the MUI interference is therefore regenerated at 213 by multiplying the latter vector by the spreading matrix W used on sending: The second (Wiener, biased) filter is then applied 20 at 205 to the observation vector obtained following subtraction 204 of this regenerated MUI interference: This second filter 205 minimizes the unconditional MSE on this estimate of the symbol sk[n] and can easily be 25 derived using the theorem of orthogonal projection: .. r ... ■ ~ "i , 30 where et us the vector of dimension K have a 1 at position \k and zeros everywhere else and where: with a] s'ituated at the position k on the diagonal and , J! eri evaluated using the following estimator: To satisfy the constraint of absence of bias, the second filter must be multiplied on the left by the " correction factor: 5 The final expression for the second filter is then obtained: The Evaluation or the symbol sk[n\ corresponds at the output of the second filter 205 to: The ariance of the residual MUI interference plus noise term %'k[n] can be evaluated via the following estimator 15 Variant 21 Overloaded regime: SUMF (Single User Matched- Filter) detection In a simplified version, the second MMSE filter at 205 may be replaced from any iteration i by a second SUMF 20 filter: The following evaluation is obtained: This approach avoids calculating N x N inverse 25 matrices. Variant 3); Non-overloaded regime In the non-overloaded situation, we have: 30 Detection amounts to applying the second filter gik=ekW at 205 to the observation vector. The '^valuation is then obtained directly from: 5.4.1.2 Aperiodic space-time (space-frequency) spreading In this case, the processing 203 may or may not include chip de-interleaving as described with reference to Figures] 9 and 10. The (canonic) Gaussian equivalent 5 multiple access model is now written: Only jiSUMF type detection is of reasonable complexity in the apejriodic context, and is therefore preferably used. 10 Variant 1:][ Overloaded regime The flilter then has the following expression: 15 Variant 2:[ Non-overloaded regime The f (liter then has the following expression: 5.4.2 Time! (or frequency) send spreading 20 The chip matrices X'(1),…,X'(B) are grouped into a unique matrix X. Following the processing 203, and with reference to Figures 9 and 10, X is reorganized into T SF X L matrices Z'(1),...,Z'(r) corresponding to T independent The observed chip matrix is denoted: (canonic) Gaussian equivalent multiple access models of 25 the type: The Matrix of the samples of noise decorrelated in 30 time: the matrix' of covariance of the residual MAI+ISI 5 interference plus noise vectors. This is made diagonal i either by\|the chip de-interleaving included in the processing 203 or by the aperiodic character of the spreading. Its diagonal elements are deduced by the variances previously estimated over the various blocks 10 processed To simplify subsequent processing (MMSE multi-user detection), a constant variance of the noise samples for the whole of the system may be assumed: The tjjemporal dependency is then eliminated: The calculations of the filters g„ for each multiple access model being similar to those described 20 above, they will not be explained here. 5.4.2.1 Periodic time (or frequency) send spreading As pireviously explained, when the spreading is periodic, jja chip interleaver (110) is used on sending, 25 and so the; processing 203 includes chip de-interleaving as described with reference to Figure 9. Variant 1 :j Overloaded regime: MMSE multi-user detection The filter,then has the following expression: 5 Variant 2:1 Overloaded regime: SUMF (Single User Matched-Filter) detection From any iteration i, the MMSE filter may be replaced ty its sub-optimum SUMF version: 10 Variant 3: Non-overloaded regime i The filter then has the following expression: 15 5.4.2.2 Periodic aperiodic time (or frequency) send spreading In this case, the processing 203 may or may not include chip de-interleaving as described with reference to Figures; 9 and 10. The T (canonic) Gaussian equivalent 20 multiple access models are now written: Only SUMF-type detection is of reasonable complexity in the aperiodic context. 25 Variant 1:1 Overloaded regime ii The kilter then has the following expression: Variant 2\\ Non-overloaded regime 30 The filter then has the following expression: 2«'>=etW(0t o» u n Other possible equalization variant: Regardless of the variants explained in sections 35 5.4.1 andjl 5.4.2, there is also a variant as to how to effect the1 second filtering 205' and the MUI interference regeneration 213' (described with reference to -M. Figure 12b), to be compared to the second filtering 205 j and the MU\|I interference regeneration 213 of Figure 12a 5 (repres en tiling these two detection steps included in the Figure 9 djr 10 scheme) . Referring to Figure 12b, the second filtering 205' is here effected upstream of the second subtraction 204 of interference regenerated at 213', rather than 10 downstrean thereof as in Figure 12a. The second filter g' used and the MUI interference reconstruction matrix b2' used may be deduced trivially from the second filter g and the MUI interference ! reconstruction matrix b2 previously computed (see above j 15 description with reference to Figures 9 or 10 and 12a), from the ijollowing condition of equality: Fromltwhich we deduce: 20 5.5 Exchajige of probabilistic information with the channel decoder On tie basis of the output of the linear filtering 25 205 with T filters, g logarithmic a posteriori probability (APP) ratios are computed at 206 for each symbol, ay. each time n = 0,...,L-l, for each user k = \,...,K . These probabilistic quantities are defined as follows: 30 and are referenced A in Figures 9, 10 and 13; or: into which we introduce: Expanding the numerator and the denominator gives: 5 The ]fikelihoods are expressed as follows: On each iteration i, a priori information on the bits of the various symbols coming from the channel decoders J!09 is available and usable in the form of 10 logarithmic APP ratios introduced beforehand and the expression for which is: Assuming space-time interleaving of sufficiently great depth, we may write: The extrinsic information on each bit delivered by weighted output demodulators 206 intended for the channel decoder 2D9 is then found at 207 from the equation: 20 All the bit extrinsic information logarithmic ratios for all tie blocks are then collected and properly multiplexed and de-interleaved at 205, to be sent to the channel decoder 209. This decoder sees a unique vector q e LI ° made up of 2 25 N0 bit intrinsic probability logarithmic ratios (one for each bit of the code word v). Decoding 206 then uses an algorithm such as the flexible output Viterbi algorithm to deliver the logarithm X of a ratio of information APP to sent nodulated data (or symbols) bits. This [Logarithm X is then the basis on which are computed at 210a and 210b the bit extrinsic information logarithmic ratios, formally defined V7 = l,...,iV0 as follows: 5 The code word extrinsic information logarithmic ratios {£/ calculated in the iteration i are similar, after bit interleaving and demultiplexing 208a and 208b, to the symbol bit APP logarithmic ratios {["l] on next iteration. 10 Reception in accordance with the invention refers not only to a method for implementing it but also to the system for executing it and any transmission system incorporating that reception system. CLAIMS 1. A reception method for communication over frequency-selective channels with a plurality of send antennas and a plurality of receive antennas, 5 characterized in that said reception method is adapted to process data received by the receive antennas that, on sending, was successively: (A) nodulated onto K channels, the number K being i strictly greater than the number T of send antennas; 10 (B) spread with an N x K periodic spreading matrix (W) or an\N x K aperiodic spreading matrix (Wn) where N is strictly Greater than T, over the K-dimensional vectors 1 of the modulated data; (C) processed to be transmitted from the T send 15 antennas; and c-it the reception method uses iteratively for this purpose: • first filtering by means of T linear filters (202, 202') adapted to process the received data, where 20 applicable after subtraction of a multi-antenna interference (MAI) and mtersymbol interference (ISI) estimate, to generate an evaluation (x) of the chips sent afte:: the spreading of the step (B) , this first filtering J taking account in particular of the spatial • before or after said first filtering, first subtracting of interference (201) using an estimate of multi-ant=nna interference (MAI) and intersymbol interference (ISI) previously regenerated from 30 information computed on the basis of an evaluation (s) of the sent modulated data generated by a previous filtering operation!'; 25 diversity of the plurality of receive antennas; • processing (203) that is the converse of that of the sendiig step (C), using a reorganization of the chips 3 5 (x) evaluated previously; • second filtering by means of K linear filters (205, 205'!') adapted to process the evaluation of the chips (x) sent obtained in this way, where appropriate after subtracting an estimate of multi-user interference; (MUI), to generate an evaluation (s) of the sent modulated data before the spreading of the step (B), this 5 second fitering taking account in particular of the i spatial diversity of the plurality of receive antennas; • before or after said second filtering, second substraction of interference (204) that uses an MUI interference estimate previously regenerated from 10 information calculated on the basis of an evaluation (s) of the sent modulated data generated by previous filtering • processing to generate an MAI+ISI interference estimate and an MUI interference estimate from the data 15 received, on the basis of information calculated on the basis of isaid evaluation (s) of the sent modulated data, the MAI+IiBl interference estimate and the MUI interference estimate being then sent recursively to the next firsj; subtraction (201) and the next second 20 subtraction (204) , respectively. 2. A reception method according to claim 1, characterized in that tie send spreading of the step (B) is effected with K strictly greater than N. 25 3. A method according to either of the preceding claims, characterized in that the reception method is adapted to process data that, on sending, was spread during the step (B) , independently for each antenna and with a number of 30 channels per antenna strictly greater than 1, the spreading, matrix (W, Wn) is a diagonal block matrix with a number ofj blocks equal to the number of antennas, and the blocks are constructed from N/T orthogonal codes. 35 4. A meth'dd according to either claim 1 or claim 2, characterized in that the reception method is adapted to process data that, on sending, was spread during the step (B) by means of a spreading full matrix (W, Wn) constructed from N-orthogonal codes. 5. A reception method according to any one of the 5 preceding claims, characterized in that the T first filters are derived using the criterion of minimizing the mean square error (MMSE), the T first filters being invariant in time for a given channel. 10 6. A reception method according to any one of claims 1 to 4, characterized in that the T first filters are matched filters (commonly called single-user matched filters (SUMF)). 15 7. A reception method according to any one of claims 1 to 4, characterized in that the T first filters are first derived in accordance with the criterion of minimizing the mean square error (MMSE), and then become matched filters ((commonly called single-user matched filters 20 (SUMF)) flfom a given iteration. 8. A reception method according to any one of claims 1 to 7, characterized in that the spreading of the send step (B) is effected periodically, the step (C) comprises chip 25 interleaving, the K second filters are derived in accordance with the unconditional criterion of minimizing the mean square error, and the K first filters are invariant in time for a given channel. 30 9. A reception method according to any one of claims 1 to 7, characterized in that the K second filters are matched filters commmonly called single user matched filters (SUMF). 35 10. A reception method according to any one of claims 1 to 7, characterized in that the spreading of the sending step (B) is effected periodically, the step (C) comprises chip interleaving, and the K second filters are first derived ini accordance with the unconditional criterion of minimizing the mean square error (the K second filters thus being invariant in time for a given channel), and 5 then become K matched filters (commonly called single-user matched filters (SUMF)) from a given iteration. 11. A rece'ption method according to any one of the 10 preceding claims, characterized in that the T first filters take account in particular of the spatial diversity Df the plurality of receive antennas by maximizing the signal-to-noise ratio (SNR) after filtering (202) . 15 12. A reception method according to any one of the preceding claims, characterized in that the first and/or second filfters are computed using sliding windows. 20 13. A reception method according to any one of the preceding claims, characterized in that the spreading of the sendir.g step (B) is effected aperiodically and the processing of the sending step (C) comprises multiplexing onto the 'I1 send antennas without interleaving, and in 25 that said converse processing (203) on reception then comprises demultiplexing onto N channels. 14. A reception method according to any one of claims 1 to 12, characterized in that the processing of the 30 sending step (C) comprises multiplexing onto one channel, chip interleaving and then demultiplexing onto the T send antennas, and in that said converse processing on reception then comprises multiplexing onto one channel, chip de-interleaving, and then demultiplexing onto N 35 channels. 15. A reception method according to any one of the preceding (claims, characterized in that, on sending, the data was coded before the step (A) , and in that, on reception, said processing to generate interference 5 estimates uses: • weighted output processing (206) processing the evaluation1! (s) of the sent modulated data and generating modulated data bit probabilistic information usable for decoding ; 10 • decoding (209) to generate a probabilistic quantity (X) from said probabilistic information; MUI interference regeneration (213, 213') generating an MUI interference estimate on the basis of this probabilistic quantity (X) this interference estimate 15 then being sent recursively to the next second • subtraction step (204); - MAJ+ISI interference regeneration (216, 216') to generate ch MAI+ISI interference estimate on the basis of the probabilistic quantity (X) and by means of 20 processing (215) conforming to that of the step (C), this interferesce estimate then being sent recursively to the next first subtraction step (201) . 16. A reception method according to claim 15, 25 character: zed in that the regeneration of MAI+ISI and MUI interferer.ee generates interference estimates from an estimate S) of the sent modulated data, which estimate (S) is computed (212) in the sense of the criterion of minimizing the mean square error (MMSE) on the basis of 30 extrinsic information (\) that is a function of bits sent previously available after decoding (209). 17. A reception method according to any one of claims 1 to 14, characterized in that, on sending, the data was 35 coded and' interleaved before the step (A), and, on reception), said processing to generate interference estimates]! uses: • weighted output processing (206) based on the evaluation of the sent modulated data (S ) and decoding statisticsj (EL) resulting from decoding (209) to generate a statistic (A) per modulated data bit; 5 • de-linterleaving (208) at the extrinsic statistics i bit level (H) found from the probabilistic quantity (A) generated previously; • weighted input and output decoding (209) on the basis of tihe data de-interleaved in this way ( 10 produce a probabilistic quantity (X) over all of the bits; • interleaving (211a-211b) at the extrinsic statistics bit level (\) found from the probabilistic quantity (X) , the new statistics (n) thus interleaved 15 then being sent recursively to the next step (206) of weighted output processing; rec-fenerating MUI interference (210, 210') to generate an MUI interference estimate on the basis of an estimate ;S) of the sent modulated data computed (212) in 20 the sense of the criterion of minimizing the mean square error (MM£E) from said new interleaved statistics (II), which MUI interference estimate is then sent recursively to, the next second subtraction step (204); • MA][+ISI interference regeneration (216, 216') to 25 generate an MAI+ISI interference estimate on the basis of the same estimate (S) of the sent modulated data by means of processing (215) conforming to that of step (C), this interference estimate then being sent recursively to the next firsiu subtraction (201) . 30 18. A reception method according to any one of claims 15 to 17, characterized in that said probabilistic quantity (X) after coding (209) is the logarithm of a ratio of modulated data bit information a priori probabilities. 35 19. A reception method according to the preceding claim, characterized in that decoding (209) computes said probabilistic quantity (A) by means of a Viterbi algorithm with weighted inputs and outputs. 20. A reception method according to any preceding claim, 5 characterized in that the spreading of the sending step (B) is effected in the frequency domain and transmission before reception is of the multicarrier type. 21. A reception method according to any one of claims 1 10 to 19, characterized in that the spreading of the sending step (B) is effected in the time domain and the transmission before reception is of the single-carrier type. 15 22. A transmission system, characterized in that it comprises:' • a sending system comprising a plurality of send antennas and adapted to modulate onto K channels, the number K being strictly greater than the number T of send 20 antennas, and to spread with an N x K periodic spreading matrix (W) or an N x K aperiodic spreading matrix (Wn) where N is strictly greater than T, over the K-dimensienal vectors of the modulated data; • a jirequency-selective transmission channel; 25 • a reception system comprising a plurality of receive antennas and adapted to implement a reception method according to any one of the preceding claims. 23. A reception system for communication over 30 frequency selective channels with a plurality of send antennas and a plurality of receive antennas, characterized in that the system is adapted to process data received via the receive antennas that, on sending, was successively: 35 (A) ihodulated onto K channels, the number K being strictly (greater than the number T of send antennas; (B) spread in the time or frequency with an N x K periodic spreading matrix (W) or an N x K aperiodic spreading jmatrix (Wn) where N is strictly greater than T, over the Rrdimensional vectors of the modulated data; 5 (C) processed to be transmitted from the T send antennas; and in that the system comprises for this purpose: • T flirst linear filters (202, 202') adapted to process the received data, where applicable after 10 subtraction of a multi-antenna interference (MAI) and intersymbol interference (ISI) estimate, to generate an evaluation (x) of the chips sent after the spreading of the step (B), this filter taking account in particular of the spatial diversity of the plurality of receive 15 antennas; • upstream or downstream of said T first filters, a first interference subtractor that uses an estimate of multi-antenna interference (MAI) and intersymbol interference (ISI) previously regenerated from 20 information computed on the basis of an evaluation (s) of the sent nodulated data generated by previous filtering; • processing means (203) adapted to execute processing that is the converse of that of the sending step (C),(using a reorganization of the chips (x) 25 evaluated(previously; t • K second linear filters (205, 205') adapted to process the evaluation of the chips (x) sent obtained in this way, where appropriate after subtracting an estimate of multi-user interference (MUI), to generate an 30 evaluation (s) of the sent modulated data before the spreading of the step (B), this second filtering taking account particular of the spatial diversity of the plurality of receive antennas; • upstream or downstream of said K second filters, a 35 second interference subtractor (204) that uses an MUI interference estimate previously regenerated from information! calculated on the basis of an evaluation (s) of the serit modulated data generated by previous filtering; • processing means for generating an MAI+ISI interference estimate and an MUI interference estimate 5 from the data received, on the basis of information calculated on the basis of said evaluation (s) of the sent modulated data, the MAI+ISI interference estimate and the MUI interference estimate being then sent recursively to the next first subtraction (201) and the 10 next second subtraction (204) , respectively, these various elements of the reception system being adapted to be used iteratively. 24. A reception system according to the preceding claim, 15 characterized in that the T first filters are derived using the (criterion of minimizing the mean square area (MMSE). 25. A rece'ption system according to claim 23, 20 characterized in that the T first filters are matched filters cqmmonly called single user matched filters (SUMF). 26. A rece'ption system according to claim 23, 25 characterized in that the T first filters are first derived in accordance with the criterion of minimizing the mean sguare error (MMSE) and then from a given iteration become T matched filters commonly called single user matched filters (SUMF). 30 27. A reception system according to any one of claims 23 to 26, characterized in that the spreading of the sending step (B) is effected periodically, the step (C) comprises chip interleaving, and the K second filters are derived 3 5 in accordance with the unconditional criterion of minimizing the mean square error, the K second filters being invariant in time for a given channel. 28. A reception system according to any one of claims 23 to 26, characterized in that the K second filters are I matched filters (commonly called single-user matched 5 filters (SUMF) ) . 29. A reception system according to any one of claims 23 to 26, characterized in that spreading of the sending step (B) is effected periodically, the step (C) comprises 10 chip interleaving, and the K second filters are first derived in accordance with the unconditional criterion of minimizing the mean square error (the K second filters being then invariant in time for a given channel), and then become K matched filters (commonly called 15 single-user matched filters (SUMF)) from a given iteration 30. A reception system according to any one of claims 23 to 29, characterized in that spreading of the sending I 20 step (B) is effected aperiodically and the processing of the sending step (C) comprises multiplexing onto the T send antennas, and in that the processing means (203) adapted to execute processing that is the converse of that of the sending step (C) then comprise a 25 demultiplexer onto N channels. 31. A reception system according to any one of claims 23 to 29, characterized in that the processing of the sending step (C) comprises multiplexing onto one channel, 30 chip interleaving and then demultiplexing onto the T send antennas, \|\|and in that the processing means (203) adapted to executes processing that is the converse of that of the sending sleep (C) then comprise a multiplexer onto one channel, la. chip de-interleaver and then a demultiplexer 35 onto N channels. 32. A reception system according to any one of the preceding claims, characterized in that, on sending, the data was coded before the step (A) and in that, on reception, said processing means for generating 5 interference estimates comprise: • weighted output processing means (206) for processing} the evaluation (s) of the sent modulated data and generating modulated data bit probabilistic information usable by a decoder; 10 • a decoder (209) for generating a probabilistic quantity IX) from said probabilistic information; • an MUI interference regenerator (213, 213') for generating an MUI interference estimate based on this probabilistic quantity (X), this interference estimate 15 then being sent recursively to the second subtractor (204); • an MAI+ISI interference regenerator (216, 216) for generating an MAI+ISI interference estimate on the basis of Uhe probabilistic quantity (X) by means of 20 processing (215) conforming to that of step (C), this interference estimate then being sent recursively to the first subtractor (201). 33. A reception system according to any one of claims 23 25 to 31, characterized in that, on sending, the data is coded and interleaved before the step (A) and in that said processing means for generating interference estimates on reception comprise: weighted output processing means (206) for 30 generating a statistic (A) for each modulated data bit from the evaluation (S) of the sent modulated data and decoding statistics (II) from a decoder (209); a de-intecleaver (208) at the bit level of extrinsic statistics (S) found from the probabilistic quantity (A) 35 generated)previously; • a one weighted input and output decoder (209) for producing from data de-interleaved in this way (q>) producing j[a probabilistic quantity (X) over all of the bits; • an interleaver (211a-211b) at the bit level of extrinsic statistics (\) found from the probabilistic 5 quantity (X) , new statistics (II) thus interleaved being then sent recursively to the weighted output processing means (206); • an MUI interference regenerator (210, 210') for generatinor an MUI interference estimate on the basis of 10 an estimate (S) of the sent modulated data, which was computed 212) in the sense of the criterion of minimizing the mean square error (MMSE) from said new interleaved statistics (II) , which MUI interference \|\| estimate 15 subtracto b (204); • MAiC+ISI interference regeneration (216, 216') to generate ian MAI+ISI interference estimate on the basis of the same estimate (S) of the sent modulated data by means of processing (215) conforming to that of step (C), this 20 interferesace estimate then being sent recursively to the first sub'tractor (201). Dated this 14th day of November, 2006 ABSTRACT The invention relates to a reception method for communication. over frequency-selective channels with a 5 plurality of send antennas and a plurality of receive antennas, to process data received by the receive antennas that, on sending, was successively modulated and spread. To this end, reception uses: 10 first linear filtering (202, 202'); • first interference subtraction (201) that uses an estimate of previously regenerated multi-antenna interference (MAI) and intersymbol interference (ISI) ; • second linear filtering (205, 205'); 15 • second interference subtraction (204) that uses an estimate G f previously regenerated multi-user interference (MUD; • processing to generate an MAI+ISI interference estimate and an MUI interference estimate for the 20 received data from the data filtered in this way. I The invention relates further to a reception system adapted to implement the method and a transmission system including)the reception system. 25

Full Text

F0RM2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003
COMPLETE SPECIFICATION
(See section 10, rule 13)
"DISJOINT ITERATIVE CHIP EQUALISATION AND MULTI-USER DETECTION FOR CDMA COMMUNICATION SYSTEMS ON A MIMO
CHANNEL"
FRANCE TELECOM French Limited Company of 6 Place d'Alleray F-75015, Paris, France
The following specification particularly describes the invention and the manner in which it is to be performed.

DISJOINT ITERATIVE CHIP EQUALISATION AND MULTI-USER DETECTION FOR CDMA COMMUNICATION SYSTEMS ON A MIMO
CHANNEL
5 GENERAL TECHNICAL FIELD
The present invention relates to the field of digital communications. It concerns how to decode efficiently digital data transmitted on a frequency-selective MIMO channel at the same time as optimizing the
10 performance1complexity trade-off. Figure 1 shows an
overall method of transmission on a frequency-selective MIMO channel 300 between a sender 100 with T send antennas, delivering signals x[n] at the time n, and a receiver 200 with R receive antennas, receiving signals
15 y[n] at the time n.
GENERAL DESCRIPTION OF THE PRIOR ART
Any communications system managing the access of multiple users to the same channel by allocating specific
20 spreading codes (CDMA) is limited in capacity by multiuser interference (MUI) between users. In the context of the present invention, transmission is envisaged on a channel liable to generate other kinds of interference such as spatial multi-antenna interference (MAI) caused
25 by multiple send antennas and intersymbol interference
(ISI) caused by the frequency selectivity of the channel. On reception, these various kinds of interference are cumulative and make recovering the useful information difficult.
30 Pioneering work carried out by S. Verdu in the 1980s clearly demonstrated the benefit of exploiting the structural properties of multi-user interference (MUI), multi-antenna interference (MAI) and intersymbol interference (ISI) to improve performance for a fixed
35 load (the number of users per chip) or to improve the load for fixed performance.

73
Many types of linear detectors have been studied, capable of supporting a greater or lesser load, which load may be evaluated analytically under asymptotic conditions. Without recourse to iterative techniques,
5 the performance of these detectors falls far short of the performance of a maximum likelihood (ML) detector (for a system with or without coding).
The class of non-linear LIC-ID detectors based on linear iterative cancellation of the interference thus
10 offers an excellent trade-off between performance and complexity. LIC-ID detectors use the following functions: linear filtering, weig[n]Ted regeneration of interference (regardless of its nature), subtraction of the regenerated interference from the received signal.
15 They deliver decisions on the sent modulated data (or
symbols) with a reliability that increases in monotonous fashion with each new attempt. LIC-ID detectors which are intended to eliminate ISI (at block level) asymptotically achieve the performance of an optimum ML
20 detector with a computation complexity similar to that of a linear equalizer. LIC-ID detectors intended to combat MUI approximate the performance of the optimum ML detector with a computation complexity comparable to that of a simple linear detector.
25 A remarkable feature of LIC-ID detectors is that they can easily be combined with hard or weig[n]Ted decisions delivered by the channel decoder, thus effecting separate and iterative detection and decoding of the data.
30 For CDMA systems that are overloaded (by hypothesis by MUI) transmitting on frequency-selective MIMO channels, the level of interference is such that using LIC-ID receivers proves essential. If an iterative strategy is selected, the complexity of the receivers can
35 be reduced, and rendered reasonable, only by simplifying the iterative processing as much as possible. LIC-ID detectors are treated separately for ISI and for MUI in

reference [1] (see below) and in the case of ISI+MUI in reference [2] (see below).
[1] A.M. Chan, G.W. Wornell, "A New Class of Efficient
5 Block-Iterative Interference Cancellation Techniques for Digital Communication Receivers", IEEE J. VLSI Signal Processing (Special Issue on Signal Processing for Wireless Communication Systems), vol. 30, pp. 197-215, Jan.-Mar. 2002.
10
[2] W. Wang, V.H. Poor, "Iterative (Turbo) Soft Interference Cancellation and Decoding for Coded CDMA", IEEE Trans. Commun., vol. COM-47, no. 9, pp. 2356-2374, Sept. 1999.
15
Their generalization to MUI+MAI+ISI still constitutes an open subject of research, in particular because of the complexity of the processing to be effected, implying computations on particularly large
20 matrices.
If a hypothesis of orthogonality exists between the various users on sending, one tempting approach is to re-establish orthogonality at the chip level before any
25 attempt at multi-user detection. Optimum multi-user
detection then amounts to a bank of filters matched to each user. This approach, developed in document [3] (see below) for a non-overloaded CDMA communications model transmitting on a frequency-selective SISO channel,
30 proves to be the optimum when aperiodic spreading is considered, for example.
[3] M. Lenardi, D.T. Slock, "A Rake Receiver with Intracell Interference Cancellation for PS-CDMA
35 Synchronous Downlink with Orthogonal Codes," IEEE VTC,
pp. 430-434, 2000.

75
The present invention goes beyond the framework of the above reference by considering an overloaded CDMA communications model transmitting on a frequency-selective MIMO channel.
5
SUMMARY OF THE INVENTION
A first aspect of the invention proposes a receiving method according to any one of claims 1 to 21.
A second aspect of the invention proposes a
10 transmission system according to claim 22.
A third aspect of the invention proposes a receiving method according to any one of claims 23 to 33.
An object of the present invention is to propose a receiver for "multicode" CDMA transmission (K > T) and1or
15 overloaded CDMA transmission (K potential users or
streams, spreading factor N 20 and a perfect knowledge of the CSI at the receiver. The
receiver is based on a combination of simple mechanisms and techniques to obtain the best possible quality of service at fixed spectral efficiency and signal-to-noise ratio (SNR) or the best possible usable bit rate at fixed
25 quality of service, band and SNR.
To this end, the invention proposes a device comprising:
• Means for guaranteeing temporal decorrelation of samples of noise affecting the chips when the multiple
30 access model with K potential users is reformed on
reception assuming the absence of MAI+ISI, said means comprising chip interleaving before transmission over the MIMO channel or aperiodic spreading. Note that although chip interleaving is not necessary for internal linear
35 aperiodic coding, it remains an option.

The invention proposes an equalization and iterative decoding device including a data detector receiving the data coming from the various send antennas comprising:
• first linear filtering processing for each send
5 antenna the MAI+ISI interference and generating
statistics on the chips sent using the spatial diversity offered by the R receive antennas;
• means for subtracting, before or after any linear
filtering associated with each send antenna, from the
10 received signal the MAI+ISI interference regenerated for that antenna from the available estimates of the sent modulated data (or symbolic data);
• means for reordering the equalized chips into a
multiple access system with K potential users in which
15 the additive noise affecting the various chips is assumed to be Gaussian white noise;
• second linear filtering processing the MUI
interference on the basis of the chips previously
equalized and reordered and generating statistics on the
20 symbolic data sent by each of the K potential users;
• means for subtracting, before or after any linear
filtering for each user, from the observed signal the MUI
interference regenerated for that user from available
estimates of the symbolic data sent;
25 • means for processing these statistics and
generating probabilistic bit information usable for external decoding;
• external decoding with weig[n]Ted inputs and
outputs, capable of generating probabilistic information
30 referred to as extrinsic information, pertinent for the calculation of the estimates of the sent symbolic data (in the sense of the criterion of minimizing the mean square error (MMSE));
• means for recursively concatenating the output of
35 the external decoder both with the MAI+ISI interference
regenerator, and with the MUI interference regenerator.

DESCRIPTION OF THE DRAWINGS
Other features and advantages of the invention will emerge from the following description, which is purely illustrative and non-limiting and should be read with
5 reference to the appended drawings in which:
• Figure 1 illustrates a general concept of transmission on a frequency-selective MIMO channel;
• Figure 2 shows a first part of a sending process, including external channel coding of digital information,
10 interleaving, and demultiplexing into K streams (one for each potential user) ;
• Figure 3 shows the second part of the Figure 2
sending process, including internal linear coding
corresponding to aperiodic space-time (space-frequency)
15 spreading followed by multiplexing onto the T send antennas;
• Figure 4 shows a second portion of the Figure 2
sending method, including internal linear coding
corresponding to aperiodic space-time (or
20 space-frequency) spreading, multiplexing onto a single channel, interleaving at chip level, and demultiplexing to the T send antennas;
• Figure 5 shows a first part of a variant of a
sending method including external channel coding of
25 digital information, interleaving, first demultiplexing (space demultiplexing) into T streams followed by second demultiplexing (code demultiplexing) into U streams;
• Figure 6 shows the second part of the Figure 5
sending method, including aperiodic time (or frequency)
30 spreading and independent multiplexing for each antenna, compatible with the UMTS HSDPA mode;
• Figure 7 shows a second portion of the Figure 4
sending method, including aperiodic time (or frequency)
spreading followed by multiplexing onto a single channel
35 and interleaving at the chip level, followed by
demultiplexing to the T send antennas, compatible with the UMTS HSDPA mode;

figure 8 shows a flat ergodic or block level fading equivalent channel obtained by decomposition of the frequency-selective MIMO channel into the Fourier base and routinely used as a model for multicarrier
5 modulations;
Figure 9 and 10 respectively show first and second variants of the architecture of a first portio of an LIC-ID receiver of the invention, in which only the functional units necessary for understanding the
10 algorithm are indicated; Figure 9 related to a sending scheme according to Figure 2-4 and 5-7 and Figure 10 relates to the sending scheme described with reference to Figure 2-3 and 5-6;
Figure 11a and 11b represent two equivalent
15 methods of implementing LIC-ID receivers for processing MAI+ISI interference, the Figure 11a implementation method representing the filtering and MaI+ISI interference regeneration parts of the first part of the overall detector shown in Figure 9 or Figure 10.
20 Figure 12 a and 12b represent receivers two equivalent methods of implementing LIC-ID receivers for processing MUI interference, the implementation method of Figure 12a representing the filtering and MUI interference regeneration parts of the first part of the overall
25 detector showm in Fiugure 9 or Figure 10;
Figure 13 shows the architecture of the second part of the LIC-ID receiver according to the invention ( the first portion of the detector being represented by Figure 9 or Figure 10), in which only the functional
30 units necessary for understanding the algorithm are indicated

DESCRIPTION OF PREFERRED EMBODIMENTS OF THE PRESENT
INVENTION
1. General structure of the sender
Reception is intimately linked to the sending mode,
5 which can be defined by a modulation1coding scheme of
high spectral efficiency, and high adaptability capacity, based on the use of spread spectrum modulation and on the use of multiple send and receive antennas. The proposed solution is pertinent assuming no knowledge of the send
10 channel (no CSI) and a perfect knowledge of the receive channel (CSI). The communications model is briefly described below in order to introduce a third embodiment of the present invention.
Referring to Figure 2 and Figure 5, the useful
15 digital data is collected and grouped into a message m of K0 bits constituting the send digital data source 101. In each message m, a linear external code C0 having an N0 x K0 generator matrix G0 and constructed on F2 assigns at 102 a code word v of length N0 bits defined by the
20 matrix equation:
v = G0 m
The external coding yield is:

The length N0 of the code words is linked to the
25 various parameters of the system by the equation:
N0 = K X L X q
in which K designates the total number of potential users, L the length of the packets (in symbol times) and q the number of bits per modulation symbol. The code may
3 0 be of any type, for example a convolutional code, a
turbocode, an LDPC code, etc. In a multiple access type configuration, the message m consists in a plurality of multiplexed messages from different sources. Coding is effected independently on each component message. The
35 code word v results from the concatenation 103 of the various code words produced.

The code word v is sent to an interleaver 104 operating at the bit level and, where appropriate, having a particular structure. In a multiple access type configuration, the interleaving acts piece by piece on
5 the various code words placed one after the other. The output of this interleaver is broken up into KL sets of g bits called integers.
The stream of integers is demultiplexed 105 onto K separate channels, where K may be chosen arbitrarily to
10 be strictly greater than the number T of send antennas. The output from this operation is a K x L integer matrix D. The L columns d[n] n = 0, ..., L-l of this matrix D have
the following structure:
d[n] = [d1[n]T d2[n]T ... dK[n]T]T F2
15 in which the component integers dk[n] k = 1, ..., K are
themselves structured as follows:

Referring to Figure 3, 4, 6, or 7, the
integers dk [n]
of the matrix D are then individually modulated 107 via a
20 modulation table :F1 to yield modulated data, or more precisely complex symbols sk[n] of a constellation with Q = 2q elements. This transforms the integer matrix D into a K x L complex matrix S the L columns s[n]
n = 0, ..., L-l whereof are structured as follows:
25 s[n]D11(d[w]) = [*,[n] s2[n] ... sK[n]J e3K
It is useful to specify the following inverse relationships:
11-'(sH)DdH frl(sk[n])Udk[n] tf (sk[n])U dkJ[n]
This is followed by internal linear coding (or spreading) 30 of the data. There are several options as to the
definition of the generator matrix W of the internal linear coding (more precisely: generator matrix of the internal linear coding on the body of the complexes) that may impact on the structure of the sender and on the
35 characteristics of the linear front-ends on reception.

Periodic spreading (or internal linear coding) where W is used again in each symbol time. To guarantee temporal decorrelation of the samples of noise affecting the chips when the multiple access system is reformed
5 after equalization, chip interleaving must be applied before transmission over the MIMO channel;
• Aperiodic spreading (or internal linear coding) where Wn depends explicitly on the symbol time. Aperiodic spreading guarantees temporal decorrelation of the
10 samples of noise affecting the chips when the multiple access system is reformed after equalization. Chip interleaving is no longer necessary but remains an option.
Moreover, the spreading may be space-time (or
15 space-frequency) spreading or only time (or frequency) spreading if it is effected independently for each antenna.
1.1 Space-time (or space-frequency) spreading (or
20 internal linear coding) under .overload conditions
Referring to Figure 3 or Figure 4, it is assumed here that aperiodic space-time (or space-frequency) spreading is effected.
The space-time (or space-frequency) spreading is
25 effected for each matrix S by means of an N x K internal
coding matrix Wn, which is denoted W in the periodic
context), where:
N = TxSF SFGD
This generator matrix is also called a spreading
30 matrix. For example, this matrix may be considered to be constructed from N orthogonal spreading codes with spreading factor N. This internal linear coding therefore corresponds, in this case, to space-time (space-frequency) spreading with spreading factor N. The
35 internal coding yield (or load) of the system is the
ratio:

The multiplication at 108 of the symbol vectors s[n]
by the generator matrix Wn produces a vector:
5 zHDW„s[n] = [z,[n] z2[n] ... z,[n]]TeD"
The relationship may also be written at the matrix level:

10 1.1.1 Spreading followed by chip interleaving
Chip interleaving is necessary if the spreading is periodic (W = Wn) in order to be able (afterwards) to implement reception in accordance with the invention. Referring to Figure 4, the chip vectors z[n]
15 n = 0,...,Z-1 are multiplexed at 109 into a single stream of chips. The chip stream then drives a chip interleaver 110, the output whereof is demultiplexed at 111 into T separate chip, streams (one for each send antenna). The effect of this operation is to transform the NxL chip
20 matrix Z:
Z = [z[0] z[l] ••• z[Z-l]]eDWxL
into a TxLSF chip matrix X:
X = [x[0] x[l] - x[LSF-1]]eUTxLS' the columns x[1] 1 = 0,---,ZS'F -1 whereof constitute the inputs 25 of the MIMO channel:
x[1] = [*,[1] x2[l] - xT[l]]J^T
1.1.2 Spreading not followed by chip interleaving Referring to Figure 3, the chip vectors z[n]
30 n = 0,...,L-1 are demultiplexed into T separate chip streams (111, one for each send antenna). The effect of this operation is to transform the NxL chip matrix Z:
Z = [z[0] z[l] - z[L-l]]eUN*L

into a TXLSF chip matrix X:

IS 13
X = [x[0] x[l] ••• x[LSF-1]]Є‮ TxLSF
the columns x[1] I = 0,---,LSF-1 whereof constitute the inputs
of the MIMO channel:
x[1] = [x,[1] x2[l] ... xT[l]TЄ‮T

5
1.2 Time (or frequency) spreading (internal linear
coding)
In this variant of the invention, shown in Figure 6
or Figure 7, compatible with the HSDPA mode of the UMTS 10 standard, there are SF orthogonal codes of length SF .
The parameter N is always a multiple of T:
N = TxSF SFЄ‮
The SF available codes are re-used at each send antenna (this is the code re-use principle). The 15 spreading, effected independently for each antenna, is
periodic or aperiodic time (or frequency) spreading (W = Wn in the periodic context).
This imposes that K be also a multiple of T:
K=TxU UeU
20 This condition, which is not limiting on the invention, yields a new expression for the internal coding yield
(load):

The generator matrix Wn has a block diagonal structure:
"w(1) o
n
NxK
;□
W(2)
25 W =

(D
w„

the block W„of the generator matrix being associated with the antenna t with dimension SF X U .
Referring to Figure 5, the integer vector d[n]
30 (demultiplexed at 105, after being coded at 102 and
interleaved at 104) sent at the time n has the following particular structure:

V51h

d[n] = [d(1)[n]T d(2)[n]T ... d{T)[n]TЄ F2qk in which the symbol vectors d(l)[n]t = l,...,T are themselves defined as follows:
d(1)[n] = [d1(t)[n]T d1(t)[n]T … d(T)[n]T]T ЄF2qk

5 Referring to Figure 5, the modulation 107 of this multiplexed data d[n] yields a modulated data (or symbols) vector sent at the time n having the following particular structure:
s[n] = [s(1)[n]T s{2)[n]T ... s(T)[n]T… [n]T]TЄ‮k
10 in which the symbol vectors s(1)[n] t = l,...,T are themselves defined as follows:
s(1)[n]= [s1(1)[n]s2(1)[n]TЄ‮U
The multiplication 108 of the symbol vector s[n] by
the generator matrix Wn produces the vector:
15 z[n]‮Wns[n]
which also has a particular structure:
z(1)[n]‮WnS[n]T z(2)[n]T ... z(T)[n]T]TЄ‮N
in which the chip vectors z(1)[n] t = 1,...,T are themselves
defined as follows:
20 z(1)[n]‮Wn(t)s(t)[n]= [z1(t)[n] z2(t)[n] ... z(t)sF [n]]TЄ‮
1.2.1 Spreading followed by chip interleaving
Chip interleaving is necessary if the spreading is periodic (W = Wn) in order to be able (afterwards) to 25 implement reception in accordance with the invention. Referring to Figure 7, the chip vectors z[n]
n = 0,...,L-l are multiplexed at 109 into a single stream of chips. The chip stream then drives a chip interleaver 110, the output whereof is demultiplexed at 111 into T 30 separate chip streams (one for each send antenna). The effect of this operation is to transform the NxL chip matrix Z:
Z = [z[0] z[l] ••• z[L-l]]Є‮NxL

into a TxLSF chip matrix X:
X = [x[0] x[l] - x[LSF-1]]Є‮TxLSr
the columns x[1] I = 0,---,LSF -1 whereof constitute the inputs
of the MIMO channel:
5 x[1] = [x1[1] x2[l] ….. xT[1]]TЄ‮T
1.2.2 Spreading not followed by chip interleaving
Referring to Figure 6, the chip vectors z(t) [n] are
then multiplexed at 109-t onto the send antenna t.
10 It will be noted that, in this sending variant, the recovery of the spatial diversity is effected via the code G0 (at 102) and external bit interleaving (at 104). The overload capacity, which is known to increase with the length of the spreading codes, is lower.
15 The sending method fits naturally into the general
class of space-time codes. The spectral efficiency of
the system (in bits per use of the channel), assuming a
limited band ideal Nyquist filter, is equal to:
η = TXp0XqXa
20 In practice, the send shaping filter has a non-null overflow factor (roll-off) e. At the receiver, a filter matched to this send filter could be used for all the receive antennas. It is assumed that the channel estimation and timing and carrier synchronization
25 functions are implemented so that the coefficients of the impulse response of the channel are regularly spaced by an amount equal to the chip time (channel equivalent in the discrete baseband to the discrete time). This hypothesis is legitimate, the Shannon sampling theorem
30 imposing sampling at the rate {1 + Є)/ Tc which may be
approximated by 1/TC when e is small. Direct
generalization is possible for expressions given below for a sampling rate equal to a multiple of 1/Tc .
35 2. Channel model
Transmission is effected on a frequency-selective

B-block. channel with multiple inputs and multiple outputs (MIMO):
H‮{H(1),H(2),...,H(B)}
The channel H(b) is assumed constant over Lx chips
5 with the convention:
LXSF=BXLx BЄ‮
The chip matrix X may be segmented into B separate TxLx chip matrices X(1),...,X(S) (padded on the rig[n]T and
left with physical zeros or guard times if necessary), 10 each matrix X(i) seeing the channel H(A) .
The extreme cases of the B-block model are as follows:
B = 1 and Lx = LSF => Ls = L quasi - static model
B = LSF and Lx = 1 => Ls = 1 ergodic (chip) model
15 A renumbering of the chips is applied within each block.
2.1 Convolutional channel model
For any block index b, the discrete time baseband
2 0 equivalent channel model (chip timing) is used to write
the receive vector y(A)[1]en" at the chip time 1 in the
form:
ywM=ZH where P is the constraint length of the channel (in 25 chips), x(b)[l]Є‮T is the complex vector of T chips sent at
the chip time 1, where HP(b)Є‮RXT is the matrix coefficient
indexed p of the impulse response of the block MIMO channel indexed b, and v(6)[1]Є‮T is the complex additive
noise vector. The complex additive noise vectors v(A)[1]
3 0 are assumed to be independent and identically distributed
in accordance with an R-dimensional Gaussian law of circular symmetry with zero mean and covariance matrix G2I. The P coefficients of the impulse response are RxT complex matrices, the inputs of which are
35 identically distributed independent Gaussian inputs, with

zero mean and with a covariance matrix satisfying the global power normalization constraint:

p-1
[P'O

= 71

in the case of a system with power equally distributed between the send antennas. Given these hypotheses, the eigen values of the correlation matrices of the coefficients of the MIMO channel conform to a Wishart distribution. It is emphasized that equal distribution of the power to the send antennas is a legitimate power allocation policy in the case of an absence of knowledge of the sending channel (no CSI).

2.2 Block matrix channel model
To introduce the data decoding algorithm, we must show a matrix system on the set of the type:
T(b) =n(*)x(*)+vw
y(
where:

ywn[y(A)[^-i+^-i]T y{b)[Lx-2+p-1f - y^[o]T

eD

(Lx+P-l)R

,(*)!

[v{b)[Lx-1 + P-1f v{h)[Lx-2 + P-1f ... v(A)[0]T]T6D(L^-1)1?

x(6)D

>[I„-1]T *W[LX-2]J

A>>)

[of

s D LxT

r(ft)
and where FT' is the Sylvester matrix for the channel

(ft)
HI")
H-!

H

(4) _

H

(ft)

(ft)
(ft)
(ft) H 0 Hl

H

(ft)

H

(ft)

. r-| (is+M)RSFxZ.Jref.

H

(ft)

H

(ft)

H

(ft)

H (ft)
H

10

2.3 Sliding window matrix channel model
In practice, to reduce the dimensions, a .sliding
window model is -used of length:
Lw = Ll+L2+1‮ Ls
The following new system is obtained: ywH = y(i)x(A)H+Y(6)[n]
where:
L„,R
□
(L,,+P-1)T
eD
UvR
f>[1] = [yH1 + A]T -. y(A)[1-Z2]T x(A)[1] = [x(*)[1 + Z1]T ••■ x(A)[1-Z2-P + lf v(A)[1] = [v(A)[1 + A]T — v(A) [1-ZjT

and where Hl,is the Sylvester matrix for the channel 300

H

(A) _

l"H?> H H(n) H ...
H?>

(A)
(A)
H
H

H

(A) P-1.

eQ

l^RSp^Lff+M^p

20

3. Multipath MIMO channel single-carrier transmission
(HSDPA)
It is assumed here that the bit rate is very high
and that the coherence time of the channel is long, so that LxD SF . For the HSDPA mode of the UMTS standard,
the channel is quasi-static, i.e. B = 1.

4. Multipath MIMO channel multicarrier transmission (MC-CDMA)
25 The spreading (or internal linear coding) is
space-frequency spreading or frequency spreading. With reference to Figure 8, it is well known to the person skilled in the art that the introduction of a send IFFT 120 and a receive FFT 220 yields (ignoring interleaving)
30 an equivalent channel that is not frequency selective (channel modeled by a circulating matrix using cyclic prefixes, then rendered diagonal in the Fourier base).

Accordingly, each carrier sees a flat MIMO channel.
Using the; formalism previously described, the channel
after FFT may be seen as a non-selective B-block channel
(P = 1). The width of the sliding window for calculating 5 the filters is lw=1.
5. General structure of the receiver 200
The iterative receiver 200 is divided into successive interference cancellation stages. A first
10 stage cancels MAI+ISI interference at chip level and
attempts to re-establish orthogonality within groups of users over all the antennas. The second stage cancels MUI interference once orthogonality has been re-established within the groups of users. The two
15 stages are activated several times. Given the scale of the problem, only linear approaches based on Wiener filters (MMSE criterion) or simple (single-user) matched filters are envisaged. In both cases, a weighted version of the interference is removed before or after filtering.
20
5.1 Sent symbol MMSE estimation
On any iteration i, there is assumed an a priori knowledge of the data expressed via logarithmic ratios on the bits of the sent symbols (also referred to as
25 modulated data):

By convention, these ratios have the value 0 on the first iteration.
Referring to Figure 9 or Figure 10, on the basis of
30 this a priori information, there can be found at 212 the matrix S' of the estimates, in the sense of the MMSE criterion, of the symbols sk[n] sent by the users k = 1,...,K
at the times n = 0,...,L-l . The estimate of a symbol is
expressed as follows:
35 3MQ5>xPr'|>*M=*]
se3

With deep space-time interleaving, the a priori probability, for a symbol may be approximated by the product of the marginal probabilities of the bits that constitute it:
5
equality being obtained for an infinite interleaving depth.
To introduce the logarithmic ratio ^j[n] of the bit
a priori probabilities previously defined, we may write:

10

and finally find:

5.2 Sent chip MMSE estimation
15 From estimated symbolic data vectors s"'[n], there may
be created at 214 (by applying to the estimates the spreading matrix Wn used on sending) the chip vectors estimated on each iteration i:
?H = w„?'[n]=[z;H j'2[n] ... J;H]T
20 that constitutes the estimated matrix Z'
This is followed by processing 215 (which may comprise multiplexing, demultiplexing, chip interleaving, block division).
The processing 215 conforms to that applied on
25 sending downstream of spreading 108 (see any of Figures 3,4,6 and 7).
For example, if the send processing comprises simple multiplexing to the T send antennas, as shown in Figures 3 and 6, the processing 215 comprises multiplexing onto T
30 channels (shown in Figure 10).
For example, if the send processing comprises multiplexing 109 onto one channel followed by chip interleaving 110 and demultiplexing (111) to the T send

10

antennas, as shown in Figures 4 and 7, the receive processing ,215 comprises multiplexing onto one channel, chip interleaving and demultiplexing onto T channels (shown in Figure 9)
5.
Following the processing 215, there are then generated (deduced from 11) the matrices Xi(1),...,Xi(B) the
columns whereof are the vectors:
x,(A)[1]=[x;w[1] x'{b)[i] - Jc;(A)[1]]TeDr
that are used for the linear iterative cancellation of the MAI+ISI interference at 201.

15

5.3 Re-establishing orthogonality between user groups by equalization to the chip time
This section considers a given block of index b that was sent by the antenna t, assuming identical processing for all of them. The invention suggests replacing optimum detection of the chips x,[l] (in the sense of the

MAP enter

ion) by an estimate in the sense of the

25

From ]the vector of the estimates of the chips on the iteration si:"

the modifiled version is defined at 216, including a 0 at 5 position Ii^T+t , which is used to regenerate the MAI+ISI
ij
interference 216 for the symbol *,[/]:

An estimate of MAI+ISI interference is therefore regenerated at 216 by multiplying this vector by said 10 Sylvester matrix H (its calculation is described above
in section 2.2 or 2.3):

The first (Wiener) filter 202 is applied to the observation vector obtained after subtraction at 201 of 15 the regenerated MAI+ISI interference:

This first filter 202 minimizes the unconditional MSE on the (biased) estimate of the chip xt[l] and may
easily be derived from the orthogonal projection theorem:

where e, ils the vector of dimension {L^+P-YyT having a 1 at positioin LT + t and zeroes everywhere else and where:
S; □ E\(x[l]-% [t])(*[l]-t [']) Je □ (V+^Fx(v^-Dr S^dijigj^-ai2)!,...,^-^2)!,^^-^2)!,....^-^2)!}
25 with the term (J ' ^
diagonal nnd &T evaluated using the following estimator:

To satisfy the absence of bias constraint, the filter must be multiplied on the left by the correctior 30 factor:

The 'Eollowing final expression for the filter is obtained:

Alternatively, this filter may be replaced, completely] or from a different iteration i (i > 1), by its single'l user matched filter (SUMF) version, given by:

The evaluation of the chip xt[/] then corresponds, at the outputj °f the first filter 202, to:

The variance of the residual MAI+ISI interference 10 plus noise is then equal to:

and may in practice be evaluated using the following estimator:

15
Other possible equalization variant:
j Figuie lib shows a variant of the first filtering
202' and the regeneration of MAI+ISI interference 210',
to be compared with the first filtering 202 and the i 20 regeneration of MAI+ISI interference 210 of Figure 11a
(representing these two detection steps included in the
|| Figure 9 or 10 scheme).
II Referring to Figure lib, here the first filtering
202' is eilfected upstream of the first subtraction 201 of
25 the MAI+ISil interference regenerated at 210', and not
downstream thereof as is the case in Figure 11a.
The ilirst filter f' used and the MAI+ISI
interference reconstruction matrix here denoted bi' used
P .
can be deduced trivially from the first filter f and the
30 MAI+ISI interference reconstruction matrix here denoted bi
If previously calculated (see above description with
reference to Figures 9 or 10 and 11a), from the following
equation:

In o"r[der then to deduce therefrom:

5.4 Equivalent Gaussian multiple access and multi-user 5 detection[model
The tjwo situations distinguished on sending (i.e. space-time (space-frequency) spreading, and time (or frequency) spreading) produce 1 or T different multiple access models.
10
5.4.1 Spac'je-time (or space-frequency) send spreading Referring to Figures 9 and 10, the chip matrices
X'(1),...,X'(B) are here grouped into a single matrix X , which
in turn is reorganized, after processing 203, into a 15 single NxL matrix Z'; the processing 203 corresponds to
the converse of the processing 215 described in section
5.2.
There! is then obtained a (canonic) Gaussian equivalent.! multiple access model of the type:

20

The observed chin matrix is denoted:
~z[[0] f|[l] - z[[L-l] Z'=[i'[0] f[l] - V[L-l]]= *'2\°] *'2\l] "' *'2[L~l] eDM
j'N[o] m ... 4[z-i]_

The riiatrix of samples of noise in time is denoted:

25 For each time n, we set:

The matrdJ! of covariance of the residual MAI+ISI interference plus noise vectors. This is made diagonal either thonks to the chip de-interleaving included at 203 or the aperiodic nature of the spreading. Its diagonal 5 elements o[re deduced from the variances previously estimates

To simplify subsequent processing (MMSE multi-user detection , a variance of the noise samples that is 10 constant : or the whole of the system may be assumed:

The Uemporal dependency is then eliminated: "■»[«] v « v«-u,...,i, l
5.4.1.1 Periodic space-time (space-frequency) send
15 spreading
As seen above, when the spreading is periodic, a chip inte;rleaver (110) is used on sending, so that the processing 203 includes chip de-interleaving (see Figure 9)
20
Variant l|i Overloaded regime: MMSE multi-user detection Here]! the optimum detection of the symbols sk[n] (in
the sense of the MAP criterion) is replaced by a non-biasei MMSE evaluation the complexity whereof is 25 polynomial in the parameters of the system and not
exponential. On each iteration i, for each potential user k, tiaere is calculated at 204 a second filter g^eD"
which, on the basis of an updated observation (relating to the column indexed n of the preceding model), 30 eliminates the MUI interference corrupting the symbol sk[n] and (produces an evaluation s'k[n] of the sent
modulated! data (or symbols) that minimizes the mean square erjror (MSE) :

subject tdf the constraint of the absence of bias. An unconditional MSE would be preferable for reasons ofo complexity: the second filter g'^. is then invariant in
time for the block concerned of the particular channel 5 (i.e. calculated once and for all over the whole of the block beiisg processed) .

From the vector of the estimates of the symbols at the iteration i:

10 it is possible to define at 213 the modified version, including a 0 at position k, that is used for the regeneration 213 of the MUI interference for the symbol

An estimate of the MUI interference is therefore regenerated at 213 by multiplying the latter vector by the spreading matrix W used on sending:

The second (Wiener, biased) filter is then applied 20 at 205 to the observation vector obtained following
subtraction 204 of this regenerated MUI interference:

This second filter 205 minimizes the unconditional MSE on this estimate of the symbol sk[n] and can easily be
25 derived using the theorem of orthogonal projection:
.. r* ... ■ ~ "i ,

30

where et us the vector of dimension K have a 1 at

position \k and zeros everywhere else and where:

with a] s'ituated at the position k on the diagonal and
, J!
eri evaluated using the following estimator:

To satisfy the constraint of absence of bias, the
second filter must be multiplied on the left by the "
correction factor:

5 The final expression for the second filter is then obtained:

The Evaluation or the symbol sk[n\ corresponds at the output of the second filter 205 to:

The ariance of the residual MUI interference plus noise term %'k[n] can be evaluated via the following
estimator

15
Variant 21 Overloaded regime: SUMF (Single User Matched-
Filter) detection
In a simplified version, the second MMSE filter at 205 may be replaced from any iteration i by a second SUMF 20 filter:

The following evaluation is obtained:

This approach avoids calculating N x N inverse 25 matrices.
Variant 3); Non-overloaded regime
In the non-overloaded situation, we have:

30 Detection amounts to applying the second filter gik=ekW at 205 to the observation vector.
The '^valuation is then obtained directly from:

5.4.1.2 Aperiodic space-time (space-frequency) spreading
In this case, the processing 203 may or may not include chip de-interleaving as described with reference to Figures] 9 and 10. The (canonic) Gaussian equivalent
5 multiple access model is now written:

Only jiSUMF type detection is of reasonable complexity in the apejriodic context, and is therefore preferably used.
10
Variant 1:][ Overloaded regime
The flilter then has the following expression:

15 Variant 2:[ Non-overloaded regime
The f (liter then has the following expression:

5.4.2 Time! (or frequency) send spreading
20 The chip matrices X'(1),…,X'(B) are grouped into a
unique matrix X. Following the processing 203, and with reference to Figures 9 and 10, X is reorganized into T SF X L matrices Z'(1),...,Z'(r) corresponding to T independent

The observed chip matrix is denoted:

(canonic) Gaussian equivalent multiple access models of 25 the type:
The Matrix of the samples of noise decorrelated in
30 time:

the matrix' of covariance of the residual MAI+ISI
5 interference plus noise vectors. This is made diagonal i either by|the chip de-interleaving included in the
processing 203 or by the aperiodic character of the
spreading. Its diagonal elements are deduced by the
variances previously estimated over the various blocks
10 processed

To simplify subsequent processing (MMSE multi-user detection), a constant variance of the noise samples for the whole of the system may be assumed:

The tjjemporal dependency is then eliminated:
The calculations of the filters g„ for each

multiple access model being similar to those described
20 above, they will not be explained here.
5.4.2.1 Periodic time (or frequency) send spreading As pireviously explained, when the spreading is periodic, jja chip interleaver (110) is used on sending, 25 and so the; processing 203 includes chip de-interleaving as described with reference to Figure 9.
Variant 1 :j Overloaded regime: MMSE multi-user detection The filter,then has the following expression:

5 Variant 2:1 Overloaded regime: SUMF (Single User Matched-Filter) detection
From any iteration i, the MMSE filter may be replaced ty its sub-optimum SUMF version:

10
Variant 3: Non-overloaded regime i The filter then has the following expression:

15 5.4.2.2 Periodic aperiodic time (or frequency) send spreading
In this case, the processing 203 may or may not include chip de-interleaving as described with reference to Figures; 9 and 10. The T (canonic) Gaussian equivalent
20 multiple access models are now written:

Only SUMF-type detection is of reasonable complexity in the aperiodic context.
25 Variant 1:1 Overloaded regime ii The kilter then has the following expression:

Variant 2\\ Non-overloaded regime 30 The filter then has the following expression:
2«'>=etW(0t
o» u n
Other possible equalization variant:
Regardless of the variants explained in sections 35 5.4.1 andjl 5.4.2, there is also a variant as to how to

effect the1 second filtering 205' and the MUI interference
regeneration 213' (described with reference to -M.
Figure 12b), to be compared to the second filtering 205
j
and the MU|I interference regeneration 213 of Figure 12a
5 (repres en tiling these two detection steps included in the
Figure 9 djr 10 scheme) .
Referring to Figure 12b, the second filtering 205' is here effected upstream of the second subtraction 204 of interference regenerated at 213', rather than
10 downstrean thereof as in Figure 12a.
The second filter g' used and the MUI interference reconstruction matrix b2' used may be deduced trivially from the second filter g and the MUI interference
!
reconstruction matrix b2 previously computed (see above j 15 description with reference to Figures 9 or
10 and 12a),
from the ijollowing condition of equality:

Fromltwhich we deduce:
20

5.5 Exchajige of probabilistic information with the channel decoder
On tie basis of the output of the linear filtering 25 205 with T filters, g logarithmic a posteriori
probability (APP) ratios are computed at 206 for each symbol, ay. each time n = 0,...,L-l, for each user k = \,...,K .
These probabilistic quantities are defined as follows:

30 and are referenced A in Figures 9, 10 and 13; or:

into which we introduce:

Expanding the numerator and the denominator gives:

5 The ]fikelihoods are expressed as follows:
On each iteration i, a priori information on the
bits of the various symbols coming from the channel decoders J!09 is available and usable in the form of

10 logarithmic APP ratios introduced beforehand and the
expression for which is:

Assuming space-time interleaving of sufficiently great depth, we may write:

The extrinsic information on each bit delivered by weighted output demodulators 206 intended for the channel decoder 2D9 is then found at 207 from the equation:

20 All the bit extrinsic information logarithmic ratios for all tie blocks are then collected and properly multiplexed and de-interleaved at 205, to be sent to the
channel decoder 209.
This decoder sees a unique vector q e LI ° made up of 2 25 N0 bit intrinsic probability logarithmic ratios (one for
each bit of the code word v). Decoding 206 then uses an algorithm such as the flexible output Viterbi algorithm to deliver the logarithm X of a ratio of information APP to sent nodulated data (or symbols) bits.

This [Logarithm X is then the basis on which are
computed at 210a and 210b the bit extrinsic information logarithmic ratios, formally defined V7 = l,...,iV0 as follows:

5 The code word extrinsic information logarithmic ratios {£/ calculated in the iteration i are similar,
after bit interleaving and demultiplexing 208a and 208b, to the symbol bit APP logarithmic ratios {["l] on next iteration.
10 Reception in accordance with the invention refers
not only to a method for implementing it but also to the system for executing it and any transmission system incorporating that reception system.

CLAIMS
1. A reception method for communication over frequency-selective channels with a plurality of send antennas and a plurality of receive antennas,
5 characterized in that said reception method is adapted to process data received by the receive antennas that, on sending, was successively:
(A) nodulated onto K channels, the number K being i strictly greater than the number T of send antennas;
10 (B) spread with an N x K periodic spreading matrix
(W) or an\N x K aperiodic spreading matrix (Wn) where N is
strictly Greater than T, over the K-dimensional vectors
1 of the modulated data;
(C) processed to be transmitted from the T send

15 antennas;
and c-it the reception method uses iteratively for
this purpose:

• first filtering by means of T linear filters (202,
202') adapted to process the received data, where
20 applicable after subtraction of a multi-antenna

interference (MAI) and mtersymbol interference (ISI)
estimate, to generate an evaluation (x) of the chips
sent afte:: the spreading of the step (B) , this first
filtering J taking account in particular of the spatial
• before or after said first filtering, first subtracting of interference (201) using an estimate of multi-ant=nna interference (MAI) and intersymbol interference (ISI) previously regenerated from
30 information computed on the basis of an evaluation (s) of
the sent modulated data generated by a previous filtering
operation!';
25 diversity of the plurality of receive antennas;
• processing (203) that is the converse of that of
the sendiig step (C), using a reorganization of the chips
3 5 (x) evaluated previously;
• second filtering by means of K linear filters
(205, 205'!') adapted to process the evaluation of the

chips (x) sent obtained in this way, where appropriate
after subtracting an estimate of multi-user interference;
(MUI), to generate an evaluation (s) of the sent
modulated data before the spreading of the step (B), this
5 second fitering taking account in particular of the i spatial diversity of the plurality of receive antennas;
• before or after said second filtering, second substraction of interference (204) that uses an MUI interference estimate previously regenerated from
10 information calculated on the basis of an evaluation (s) of the sent modulated data generated by previous filtering
• processing to generate an MAI+ISI interference
estimate and an MUI interference estimate from the data
15 received, on the basis of information calculated on the
basis of isaid evaluation (s) of the sent modulated data,
the MAI+IiBl interference estimate and the MUI
interference estimate being then sent recursively to the
next firsj; subtraction (201) and the next second
20 subtraction (204) , respectively.
2. A reception method according to claim 1, characterized in that tie send spreading of the step (B) is effected with K strictly greater than N.
25
3. A method according to either of the preceding claims, characterized in that the reception method is adapted to process data that, on sending, was spread during the step (B) , independently for each antenna and with a number of 30 channels per antenna strictly greater than 1, the
spreading, matrix (W, Wn) is a diagonal block matrix with a number ofj blocks equal to the number of antennas, and the blocks are constructed from N/T orthogonal codes.
35 4. A meth'dd according to either claim 1 or claim 2,
characterized in that the reception method is adapted to process data that, on sending, was spread during the step

(B) by means of a spreading full matrix (W, Wn) constructed from N-orthogonal codes.
5. A reception method according to any one of the
5 preceding claims, characterized in that the T first
filters are derived using the criterion of minimizing the mean square error (MMSE), the T first filters being invariant in time for a given channel.
10 6. A reception method according to any one of claims 1 to 4, characterized in that the T first filters are matched filters (commonly called single-user matched filters (SUMF)).
15 7. A reception method according to any one of claims 1 to
4, characterized in that the T first filters are first
derived in accordance with the criterion of minimizing
the mean square error (MMSE), and then become matched
filters ((commonly called single-user matched filters
20 (SUMF)) flfom a given iteration.
8. A reception method according to any one of claims 1 to 7, characterized in that the spreading of the send step (B) is effected periodically, the step (C) comprises chip
25 interleaving, the K second filters are derived in
accordance with the unconditional criterion of minimizing the mean square error, and the K first filters are invariant in time for a given channel.
30 9. A reception method according to any one of claims 1 to 7, characterized in that the K second filters are matched filters commmonly called single user matched filters (SUMF).
35 10. A reception method according to any one of claims 1 to 7, characterized in that the spreading of the sending step (B) is effected periodically, the step (C) comprises

chip interleaving, and the K second filters are first derived ini accordance with the unconditional criterion of minimizing the mean square error (the K second filters thus being invariant in time for a given channel), and
5 then become K matched filters (commonly called single-user matched filters (SUMF)) from a given iteration.
11. A rece'ption method according to any one of the
10 preceding claims, characterized in that the T first filters take account in particular of the spatial diversity Df the plurality of receive antennas by maximizing the signal-to-noise ratio (SNR) after filtering (202) .
15
12. A reception method according to any one of the preceding claims, characterized in that the first and/or second filfters are computed using sliding windows.
20 13. A reception method according to any one of the
preceding claims, characterized in that the spreading of the sendir.g step (B) is effected aperiodically and the processing of the sending step (C) comprises multiplexing onto the 'I1 send antennas without interleaving, and in
25 that said converse processing (203) on reception then comprises demultiplexing onto N channels.
14. A reception method according to any one of claims 1
to 12, characterized in that the processing of the
30 sending step (C) comprises multiplexing onto one channel, chip interleaving and then demultiplexing onto the T send antennas, and in that said converse processing on reception then comprises multiplexing onto one channel, chip de-interleaving, and then demultiplexing onto N
35 channels.

15. A reception method according to any one of the preceding (claims, characterized in that, on sending, the data was coded before the step (A) , and in that, on reception, said processing to generate interference
5 estimates uses:

• weighted output processing (206) processing the evaluation1! (s) of the sent modulated data and generating modulated data bit probabilistic information usable for decoding ;
10 • decoding (209) to generate a probabilistic quantity (X) from said probabilistic information; MUI interference regeneration (213, 213') generating an MUI interference estimate on the basis of this probabilistic quantity (X) this interference estimate
15 then being sent recursively to the next second • subtraction step (204);
- MAJ+ISI interference regeneration (216, 216') to generate ch MAI+ISI interference estimate on the basis of the probabilistic quantity (X) and by means of
20 processing (215) conforming to that of the step (C), this interferesce estimate then being sent recursively to the next first subtraction step (201) .
16. A reception method according to claim 15, 25 character: zed in that the regeneration of MAI+ISI and MUI interferer.ee generates interference estimates from an estimate S) of the sent modulated data, which estimate (S) is computed (212) in the sense of the criterion of minimizing the mean square error (MMSE) on the basis of
30 extrinsic information (\) that is a function of bits sent previously available after decoding (209).
17. A reception method according to any one of claims 1 to 14, characterized in that, on sending, the data was 35 coded and' interleaved before the step (A), and, on
reception), said processing to generate interference estimates]! uses:

• weighted output processing (206) based on the evaluation of the sent modulated data (S ) and decoding statisticsj (EL) resulting from decoding (209) to generate a statistic (A) per modulated data bit;
5 • de-linterleaving (208) at the extrinsic statistics
i
bit level (H) found from the probabilistic quantity (A) generated previously;
• weighted input and output decoding (209) on the basis of tihe data de-interleaved in this way (

10 produce a probabilistic quantity (X) over all of the bits;
• interleaving (211a-211b) at the extrinsic statistics bit level (\) found from the probabilistic quantity (X) , the new statistics (n) thus interleaved
15 then being sent recursively to the next step (206) of weighted output processing;
rec-fenerating MUI interference (210, 210') to
generate an MUI interference estimate on the basis of an
estimate ;S) of the sent modulated data computed (212) in
20 the sense of the criterion of minimizing the mean square
error (MM£E) from said new interleaved statistics (II),
which MUI interference estimate is then sent recursively
to, the next second subtraction step (204);
• MA][+ISI interference regeneration (216, 216') to
25 generate an MAI+ISI interference estimate on the basis of the same estimate (S) of the sent modulated data by means of processing (215) conforming to that of step (C), this
interference estimate then being sent recursively to the
next firsiu subtraction (201) .
30
18. A reception method according to any one of claims 15 to 17, characterized in that said probabilistic quantity (X) after coding (209) is the logarithm of a ratio of modulated data bit information a priori probabilities.
35
19. A reception method according to the preceding claim, characterized in that decoding (209) computes said

probabilistic quantity (A) by means of a Viterbi algorithm with weighted inputs and outputs.
20. A reception method according to any preceding claim, 5 characterized in that the spreading of the sending step (B) is effected in the frequency domain and transmission before reception is of the multicarrier type.
21. A reception method according to any one of claims 1
10 to 19, characterized in that the spreading of the sending
step (B) is effected in the time domain and the

transmission before reception is of the single-carrier
type.
15 22. A transmission system, characterized in that it comprises:'
• a sending system comprising a plurality of send
antennas and adapted to modulate onto K channels, the
number K being strictly greater than the number T of send
20 antennas, and to spread with an N x K periodic spreading
matrix (W) or an N x K aperiodic spreading matrix (Wn)
where N is strictly greater than T, over the
K-dimensienal vectors of the modulated data;
• a jirequency-selective transmission channel; 25 • a reception system comprising a plurality of
receive antennas and adapted to implement a reception method according to any one of the preceding claims.
23. A reception system for communication over
30 frequency selective channels with a plurality of send
antennas and a plurality of receive antennas,
characterized in that the system is adapted to process
data received via the receive antennas that, on sending,
was successively:
35 (A) ihodulated onto K channels, the number K being strictly (greater than the number T of send antennas;

(B) spread in the time or frequency with an N x K periodic spreading matrix (W) or an N x K aperiodic spreading jmatrix (Wn) where N is strictly greater than T, over the Rrdimensional vectors of the modulated data;
5 (C) processed to be transmitted from the T send
antennas;
and in that the system comprises for this purpose:
• T flirst linear filters (202, 202') adapted to process the received data, where applicable after
10 subtraction of a multi-antenna interference (MAI) and
intersymbol interference (ISI) estimate, to generate an evaluation (x) of the chips sent after the spreading of the step (B), this filter taking account in particular of the spatial diversity of the plurality of receive
15 antennas;
• upstream or downstream of said T first filters, a first interference subtractor that uses an estimate of multi-antenna interference (MAI) and intersymbol interference (ISI) previously regenerated from
20 information computed on the basis of an evaluation (s) of
the sent nodulated data generated by previous filtering;
• processing means (203) adapted to execute processing that is the converse of that of the sending step (C),(using a reorganization of the chips (x)
25 evaluated(previously;
t
• K second linear filters (205, 205') adapted to process the evaluation of the chips (x) sent obtained in this way, where appropriate after subtracting an estimate of multi-user interference (MUI), to generate an
30 evaluation (s) of the sent modulated data before the
spreading of the step (B), this second filtering taking account particular of the spatial diversity of the plurality of receive antennas;
• upstream or downstream of said K second filters, a
35 second interference subtractor (204) that uses an MUI interference estimate previously regenerated from information! calculated on the basis of an evaluation (s)

of the serit modulated data generated by previous filtering;
• processing means for generating an MAI+ISI
interference estimate and an MUI interference estimate
5 from the data received, on the basis of information
calculated on the basis of said evaluation (s) of the
sent modulated data, the MAI+ISI interference estimate
and the MUI interference estimate being then sent
recursively to the next first subtraction (201) and the
10 next second subtraction (204) , respectively,
these various elements of the reception system being
adapted to be used iteratively.
24. A reception system according to the preceding claim,
15 characterized in that the T first filters are derived using the (criterion of minimizing the mean square area (MMSE).
25. A rece'ption system according to claim 23, 20 characterized in that the T first filters are matched filters cqmmonly called single user matched filters (SUMF).
26. A rece'ption system according to claim 23, 25 characterized in that the T first filters are first
derived in accordance with the criterion of minimizing the mean sguare error (MMSE) and then from a given iteration become T matched filters commonly called single user matched filters (SUMF).
30
27. A reception system according to any one of claims 23 to 26, characterized in that the spreading of the sending step (B) is effected periodically, the step (C) comprises chip interleaving, and the K second filters are derived
3 5 in accordance with the unconditional criterion of
minimizing the mean square error, the K second filters being invariant in time for a given channel.

28. A reception system according to any one of claims 23
to 26, characterized in that the K second filters are
I matched filters (commonly called single-user matched
5 filters (SUMF) ) .
29. A reception system according to any one of claims 23 to 26, characterized in that spreading of the sending step (B) is effected periodically, the step (C) comprises
10 chip interleaving, and the K second filters are first
derived in accordance with the unconditional criterion of minimizing the mean square error (the K second filters being then invariant in time for a given channel), and then become K matched filters (commonly called
15 single-user matched filters (SUMF)) from a given iteration
30. A reception system according to any one of claims 23
to 29, characterized in that spreading of the sending I
20 step (B) is effected aperiodically and the processing of
the sending step (C) comprises multiplexing onto the T
send antennas, and in that the processing means (203)
adapted to execute processing that is the converse of
that of the sending step (C) then comprise a
25 demultiplexer onto N channels.
31. A reception system according to any one of claims 23 to 29, characterized in that the processing of the sending step (C) comprises multiplexing onto one channel,
30 chip interleaving and then demultiplexing onto the T send antennas, ||and in that the processing means (203) adapted to executes processing that is the converse of that of the
sending sleep (C) then comprise a multiplexer onto one
channel, la. chip de-interleaver and then a demultiplexer
35 onto N channels.

32. A reception system according to any one of the preceding claims, characterized in that, on sending, the data was coded before the step (A) and in that, on reception, said processing means for generating
5 interference estimates comprise:
• weighted output processing means (206) for processing} the evaluation (s) of the sent modulated data and generating modulated data bit probabilistic information usable by a decoder;
10 • a decoder (209) for generating a probabilistic quantity IX) from said probabilistic information;
• an MUI interference regenerator (213, 213') for
generating an MUI interference estimate based on this
probabilistic quantity (X), this interference estimate
15 then being sent recursively to the second subtractor
(204);
• an MAI+ISI interference regenerator (216, 216) for generating an MAI+ISI interference estimate on the basis of Uhe probabilistic quantity (X) by means of 20 processing (215) conforming to that of step (C), this
interference estimate then being sent recursively to the
first subtractor (201).
33. A reception system according to any one of claims 23 25 to 31, characterized in that, on sending, the data is coded and interleaved before the step (A) and in that said processing means for generating interference estimates on reception comprise:
weighted output processing means (206) for
30 generating a statistic (A) for each modulated data bit
from the evaluation (S) of the sent modulated data and
decoding statistics (II) from a decoder (209);
a de-intecleaver (208) at the bit level of extrinsic
statistics (S) found from the probabilistic quantity (A)
35 generated)previously;
• a one weighted input and output decoder (209) for producing from data de-interleaved in this way (q>)

producing j[a probabilistic quantity (X) over all of the bits;
• an interleaver (211a-211b) at the bit level of extrinsic statistics (\) found from the probabilistic
5 quantity (X) , new statistics (II) thus interleaved being then sent recursively to the weighted output processing means (206);
• an MUI interference regenerator (210, 210') for
generatinor an MUI interference estimate on the basis of
10 an estimate (S) of the sent modulated data, which was
computed 212) in the sense of the criterion of
minimizing the mean square error (MMSE) from said new
interleaved statistics (II) , which MUI interference
|| estimate
15 subtracto b (204);
• MAiC+ISI interference regeneration (216, 216') to generate ian MAI+ISI interference estimate on the basis of the same estimate (S) of the sent modulated data by means of processing (215) conforming to that of step (C), this
20 interferesace estimate then being sent recursively to the first sub'tractor (201).

Dated this 14th day of November, 2006

ABSTRACT
The invention relates to a reception method for
communication.
over frequency-selective channels with a
5 plurality of send antennas and a plurality of receive
antennas, to process data received by the receive
antennas that, on sending, was successively modulated and
spread.
To this end, reception uses:
10 first linear filtering (202, 202');
• first interference subtraction (201) that uses an estimate of previously regenerated multi-antenna interference (MAI) and intersymbol interference (ISI) ;
• second linear filtering (205, 205'); 15
• second interference subtraction (204) that uses an estimate G f previously regenerated multi-user interference (MUD;
• processing to generate an MAI+ISI interference
estimate and an MUI interference estimate for the
20 received data from the data filtered in this way. I The invention relates further to a reception system
adapted to implement the method and a transmission system
including)the reception system.
25

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Patent Number

250949

Indian Patent Application Number

1383/MUMNP/2006

PG Journal Number

07/2012

Publication Date

17-Feb-2012

Grant Date

09-Feb-2012

Date of Filing

16-Nov-2006

Name of Patentee

FRANCE TELECOM

Applicant Address

6 PLACE D'ALLERAY F-75015, PARIS

Inventors:

#	Inventor's Name	Inventor's Address
1	VISOZ, RAPHAEL	33 RUE DANTON, F-92130 ISSY LES MOULINEAUX
2	BERTHET, ANTOINE	72 AVENUE JEAN JAURES, BAT A, ESC.3, F-92290 CHATENAY MALABRY

PCT International Classification Number

H04B7/04,H04L1/06

PCT International Application Number

PCT/EP2005/004410

PCT International Filing date

2005-04-21

PCT Conventions:

#	PCT Application Number	Date of Convention	Priority Country
1	04291039.8	2004-04-22	EUROPEAN UNION