RECEIVER, TRANSMISSION / RECEPTION SYSTEM AND ASSOCIATED RECEPTION METHOD

Abstract

The receiver comprises: - a sampler designed to provide one or more samples (yn) per received symbol, the symbols belonging to a predefined alphabet; - an equalizer (210) designed to calculate, for each received symbol, an estimate (zn) of that symbol from a linear combination (y'n) of the samples (yn) for that symbol; and - a decision module (216) designed to determine the symbol from the alphabet closest to the estimate (zn) as the detected symbol. The alphabet exhibits decentering such that the transmitted symbols have a non-zero predefined expectation, and the equalizer (210) is designed to add a non-zero scalar component (θ) to the linear combination (y'n) to compensate at least partially for the decentering. Figure for the abstract: Fig. 4

Description

Title of the invention: RECEIVER, TRANSMISSION / RECEPTION SYSTEM AND ASSOCIATED RECEPTION METHOD Technical field of the invention

[0001] The present invention relates to the field of digital data transmissions and more particularly to equalization for digital communications.

[0002] It refers more particularly to a receiver, a transmission / reception system comprising said receiver, an associated reception process. Technological background

[0003] In a conventional manner, a digital receiver on a transmission chain includes an equalizer to reduce errors in the detection of symbols emitted by a transmitter, in the presence of noise and inter-symbol interference (ISI: "InterSymbol Interference" in English).

[0004] Symbol interference may be due to: • limited bandwidth of certain components of the transmission chain, e.g. photodetector of the receiver, attenuating or phasing some frequencies of the modulated signal more strongly than others; • a superposition at the receiver level of several echoes of the modulated signal received with distinct and proper attenuations, delays and phase shifts, typically in the case of a multipath transmission channel.

[0005] In a known manner, the receptor comprises: • a sampler designed to sample a received signal that has propagated in a propagation channel, successive symbols are encoded in this received signal, in order to provide one or more samples per received symbol, the symbols belonging to a predefined alphabet; • an equalizer designed to calculate, for each received symbol, an estimate of that symbol from a linear combination of samples for that symbol; and • a decision module designed to determine the symbol from the alphabet closest to the estimated detected symbol.

[0006] The article entitled "MMSE Decision-Feedback Equalizers and Coding - Part I: Equalization Results" by John M. Cioffi and M. Vedat Eyuboglu, published in IEEE Transactions on Communications, Vol. 43, No. 10, in October 1995, describes an example of a decision-feedback equalizer that minimizes the mean squared error (MSE). This type of filter is commonly referred to as MMSE-DFE (Minimum Mean-Squared-Error Decision-Feedback Equalizer).

[0007] The inventors have observed that a receiver using this type of equalizer may exhibit reduced reception performance (e.g., high bit error rate).

[0008] It may therefore be desirable to provide a receiver that improves reception performance. Summary of the invention

[0009] A digital data receiver comprising: is therefore proposed. • a sampler designed to sample a received signal that has propagated through a propagation channel, with successive symbols being encoded in this received signal, in order to provide one or more samples per received symbol, the symbols belonging to a predefined alphabet; • an equalizer designed to calculate, for each received symbol, an estimate of that symbol from a linear combination of samples for that symbol; and • a decision module designed to determine the symbol from the alphabet closest to the estimated detected symbol; characterized in that the alphabet exhibits decentering such that the emitted symbols have a non-zero predefined expectation, and in that the equalizer is designed to add a non-zero scalar component to the linear combination to compensate at least in part for the decentering.

[0010] Indeed, the non-centering of the modulation alphabet introduces a bias in the estimation. In particular, with a non-centered alphabet, the MMSE-DFE equalizer of the prior art mentioned above is not optimal in the sense that it does not allow minimizing the mean squared error criterion.

[0011] Adding the non-zero scalar component before the decision-making process makes it possible to compensate at least in part for the induced bias and thus obtain more efficient symbol detection, in particular by achieving a reduced bit error rate.

[0012] It follows that the decision module following the equalizer can consist of thresholds or decision regions whose value or shape is independent of the equalizer and depends solely on the modulation alphabet. Its practical implementation is thus simplified, for example, compared to the decision module of the prior art receiver described above, where the decision thresholds must be adapted to the values ​​of the equalizer coefficients.

[0013] The invention may further include one or more of the following optional features, according to any technically possible combination.

[0014] Optionally, the equalizer is designed to calculate the scalar component from coefficients of the linear combination of the samples and the predefined expectation.

[0015] Optionally also, the equalizer is designed to calculate the scalar component from a channel matrix representative of the propagation channel.

[0016] Optionally also, said channel matrix is ​​a block Toeplitz matrix.

[0017] Optionally also, the equalizer is designed to calculate said scalar component in order to minimize a mean squared error between the emitted and estimated symbols.

[0018] Optionally also, the equalizer includes a direct filter, preferably with a finite impulse response, and the equalizer is designed to apply this direct filter to the samples to provide said linear combination.

[0019] Optionally also, the equalizer is designed to calculate, for each received symbol, the estimate of that symbol independently of previously detected symbols.

[0020] Optionally also, the equalizer is designed to calculate, for each received symbol, the estimate of that symbol from a difference between the linear combination of samples for that symbol and a linear combination of previously detected symbols, the scalar component being added to this difference.

[0021] Optionally also, the equalizer further includes a so-called feedback filter, preferably with a finite impulse response, and the equalizer is designed to apply this feedback filter to the previously detected symbols so as to provide said linear combination of previously detected symbols.

[0022] Optionally, the equalizer is also designed to calculate the scalar component from the direct filter.

[0023] Optionally also, the equalizer is designed to calculate the scalar component further from the return filter.

[0024] Optionally also, the equalizer is designed to iteratively update the scalar component based on symbols previously determined by the decision module.

[0025] A digital communication system is also proposed, characterized in that it comprises a transmitter designed to emit symbols selected from an alphabet of non-zero expectation, and a receiver according to the invention.

[0026] A method for receiving digital data is also proposed, comprising: • for each of several successive symbols encoded in a received signal that has propagated through a propagation channel, the symbols belonging to a predefined alphabet, a reception of several samples; • a linear equalization by calculating, for each received symbol, an estimate of that symbol from a linear combination of the samples for that symbol; and • a determination of the alphabet symbol closest to the estimated detected symbol; characterized in that the alphabet exhibits a decentering such that the emitted symbols have a non-zero predefined expectation, in that the linear equalization involves an addition of a non-zero scalar component to the linear combination to partially compensate for the decentering.

[0027] Also proposed is a computer program downloadable from a communication network and / or recorded on a computer-readable medium, characterized in that it includes instructions for the execution of the steps of a process according to the invention, when said program is executed on a computer. Brief description of the figures

[0028] The invention will be better understood with the aid of the following description, given solely by way of example and made with reference to the accompanying drawings in which: • Fig. 1 schematically illustrates a communication system implementing the present invention; • [Fig.2] schematically illustrates a receiver according to the invention; • Figure 3 schematically illustrates an example of sampling carried out by the receiver according to the invention; • [Fig.4] schematically illustrates an example of implementing a receiver equalizer according to a first embodiment; • [Fig.5] schematically illustrates a method for configuring the equalizer of [Fig.4]; • [Fig.6] schematically illustrates an example of implementing the equalizer of a receiver according to a second embodiment; • [Fig.7] schematically illustrates a method of configuring the equalizer according to a variant of the first embodiment; • [Fig.8] schematically illustrates a method of configuring the equalizer according to a variant of the second embodiment; • Figure 9 schematically illustrates an example of equalizer implementation according to a variant of the second embodiment; and • [Fig. 10] schematically illustrates an information processing device intended to implement the invention. Detailed description of the invention

[0029] Hereafter, vectors will be indicated in bold to distinguish them from scalars. The exponent H associated with a matrix will hereafter denote the conjugate transpose of that matrix.

[0030] With reference to [Fig.1], an example of a digital communication system 100 in which the invention is implemented will now be described.

[0031] The digital communication system 100 comprises a transmitter 102, a receiver 104 and a propagation channel 106 linking the transmitter 102 to the receiver 104.

[0032] More specifically, the transmitter 102 is designed to emit a signal e(t) carrying a digital message. By definition, a digital message is a sequence of binary elements, commonly referred to as "bits" ("binary elements" in English).

[0033] The transmitter 102 is designed to successively encode, in the signal e(t), symbols sn representing respectively successive blocks or words of p bits. Each symbol sn corresponds to one or more modulations of a carrier signal at a carrier frequency, such that the modulated carrier signal forms the signal e(t). Each symbol sn belongs to an alphabet Q with K elements {So, Si,...,SK} respectively associated with the different possible combinations of bits in a word. The transmitter 102 is designed to regularly transmit the symbols according to a symbol period Ts.

[0034] In the context of the present invention, this alphabet Q is non-centered, that is to say that the symbols emitted sn have a non-zero expectation, i.e. E[s„] * 0, in particular when the data emitted lead to a substantially equiprobable selection of the elements of the alphabet Q.

[0035] Among the modulations featuring a non-centered alphabet are intensity modulations, such as on-off keying (OOK) or its K-ary generalizations (K being the number of possible intensity levels). Any other modulation can also be used, provided that the alphabet used is non-centered.

[0036] In general, it is assumed that the emitted symbols are mutually uncorrelated, that is to say that the value of an emitted symbol does not depend on the value of previously emitted symbols, and that the emitted symbols sn have a non-zero variance: o.2 = E[|s„r-]-E2[s„].

[0037] For example, in the case of an optical communication system implementing optical all-or-none (OOK) modulation, the transmitter 102 can be an amplitude-modulated laser source configured to emit a laser pulse of amplitude A at each symbol associated with bit "1" but no pulse (i.e., substantially zero amplitude) at each symbol associated with bit "0". The inverse association could also be used. In this case, the emitted symbols sn take their values ​​with equiprobability in the binary alphabet {0, A}, so that their expectation E[s„] is equal to A / 2 and their variance is equal to A2 / 4.

[0038] Generally, the propagation channel 106 is a material medium suitable for transmitting the signal e(t) emitted by the transmitter 102, for example in the form of electromagnetic waves (i.e. optical or radio frequency), so that it can be received by the receiver 104. For example, the propagation channel 106 is an optical fiber, a coaxial power line, air or water or any other natural medium suitable for transmitting, for example, an optical or radio frequency signal.

[0039] The propagation channel 106 is linear in the sense that the effects or distortions it induces on the signal are linear. To this end, the transmitter 102 is, for example, configured to transmit at a power lower than a non-linear distortion threshold of the propagation channel 106, for example a non-linear dispersion threshold.

[0040] For example, in the case of optical communication where the propagation channel 106 is an optical fiber, the optical power emitted is adapted according to the optical fiber used to avoid the non-linear effects of the fiber.

[0041] Furthermore, the propagation channel 106 is dispersive in nature, that is to say, susceptible to generating interference between symbols. For example, this is the case with a chromatic dispersion optical fiber inducing a broadening of optical pulses during propagation or with a multipath radio or optical transmission channel in which several copies of the same symbol are detected by the receiver 104 with different delays.

[0042] Furthermore, the propagation channel 106 may be affected by noise w(t), for example with zero expected value and independent of the emitted symbols sn. For example, the noise w(t) is an additive Gaussian noise centered with variance ow2.

[0043] The receiver 104 is designed to receive an analog signal r(t) corresponding to the signal emitted e(t) after propagation through the propagation channel 106.

[0044] Conventionally, the receiver 104 is configured, for example, to receive the received signal r(t) on the carrier frequency of the signal from the transmitter 102 and to transpose this signal into baseband (i.e., around a zero frequency) and filter it, for example, by applying a low-pass filter. The signal after transposition and filtering is always denoted r(t).

[0045] Knowing the alphabet Q, the receiver 104 is further designed to detect in this received signal r(t) the initially emitted symbols sn, particularly in the presence of noise and inter-symbol interference in the received signal r(t). Thus, the receiver 104 is designed to provide a detected symbol s„ for each emitted symbol sn.

[0046] With reference to [Fig.2], a first embodiment of the receiver 104 will now be described.

[0047] The receiver 104 includes a sampler 208 designed to sample the received signal r(t) and thus provide successive samples yn,m of this signal r(t).

[0048] In particular, for each symbol period Ts corresponding to the emission of a symbol sn, the sampler 208 provides a set yn of M samples yn >m (M greater than or equal to one) such that:

[0049] [Math.l] y = v /

[0050] where m is an integer index ranging from 0 to Ml, M denoting the total number of samples per symbol received during the symbol period Ts.

[0051] Fig. 3 schematically illustrates an example of a received signal r(t) and the corresponding digitized signal yn as supplied at the output of the sampler 208.

[0052] In general, the sampler 208 is configured to take M samples per symbol with a sampling period Te between each sample, such that Te=Ts / M.

[0053] In the example in [Fig. 3], the sampler 208 is configured to take two samples (M=2) per symbol period Ts. The sampling period Te is equal to half the symbol period Ts, so Te=Ts / 2. Thus, the sampler 208 provides, respectively for the three consecutive symbols sn, sn+b, and sn+2, the following three sample vectors:

[0054] [Math.2] / / ^»+1,1^ / ^«+2,11 ~ \ ' J«+1 ~ \ -W / ' J«+2 ~ /

[0055] Returning to [Fig.2], the receiver 104 further includes an equalizer 210 connected to the output of the sampler 208. The equalizer 210 is configured to provide at each symbol period Ts, an estimated zn of the symbol received from the M samples yn >m, provided by the sampler 208.

[0056] The receiver 104 further includes a noise estimator 212 connected on one side to the output of the sampler 208 and on the other side to the equalizer 210. In a conventional manner, the noise estimator 212 is configured to calculate the variance ow2 of the noise from the samples yn provided by the sampler 208 and to provide this variance to the equalizer 210.

[0057] In the present example, the noise is an additive Gaussian noise, centered (i.e., with zero mean), with variance ow2 and independent of the emitted symbols. More generally, the Noise characteristics are specific to the communication system concerned and depend in particular on the nature of the transmission channel 106. Thus, these characteristics can be adjusted according to the transmission system considered.

[0058] The receiver 104 further includes a channel estimator 214 connected on one side to the output of the sampler 208 and on the other side to the equalizer 210. The channel estimator 214 is configured on the one hand to calculate from the samples yn, a channel matrix H representing the distortions that the propagation channel 106 causes to the symbols and on the other hand to provide this channel matrix H to the equalizer 210. This matrix describes the interference pattern between symbols specific to the propagation channel concerned.

[0059] Preferably, the channel matrix H is a block Toeplitz matrix, comprising for example at least one non-zero block in the first position of the first row and first column.

[0060] The equalizer 210 is configured to receive data relating to the modulation format used by the transmitter 102 to transmit the symbols. For example, this data includes the expectation E[.v„] and / or the variance cj of the transmitted symbols sn.

[0061] The equalizer 210 will be described in more detail later, with reference to [Fig.4].

[0062] The receiver 100 further includes a decision module 216 designed to select the symbol from the alphabet Q closest to the estimated zn. The selected symbol is thus taken as the detected symbol snV where A is the restitution delay which is a parameter of the equalizer 210.

[0063] For example, the decision module 216 is designed to compare the estimated zn to regions defined by predefined thresholds, each region being respectively associated with one of the symbols of the alphabet Q. The thresholds are independent of the equalizer 210 and in particular of its coefficients p H and its scalar component 0 which will be described later.

[0064] With reference to [Fig.4], the equalizer 210 of receiver 104 of [Fig.2] will now be described in more detail.

[0065] The equalizer 210 includes a sample combiner, called direct combiner 400, designed, for each symbol period Ts, to receive the samples yn and provide a linear combination y'n of said samples.

[0066] For example, the direct combiner 400 is defined by direct coefficients p H, so that the linear combination y'n is obtained by weighting the samples yn by the direct coefficients p H, so that y'n=p Hxy n, where x is the scalar product.

[0067] For example, this direct combiner 400 is a direct filter (“feed-forward” in English), preferably a digital filter with finite impulse response (FIR: “Finite Impulse Response” in English).

[0068] The equalizer 210 further includes a configuration module 400a of the direct combiner 400, to configure the latter according to configuration parameters.

[0069] For example, these configuration parameters include channel parameters specific to the propagation channel 106, such as the channel matrix H and / or the noise variance ow2. These configuration parameters may also include parameters specific to the modulation alphabet Q, such as the variance o? of the transmitted symbols sn.

[0070] In the case where the direct combiner 400 is an FIR filter, the configuration module 400a determines the pH coefficients defining the filter. For example, this pH vector comprises NxM coefficients, so that the direct combiner 400 provides a linear combination of samples every Ts seconds.

[0071] The equalizer 210 further includes a feedback loop between the decision module 216 and the direct combiner 400, in order to improve symbol detection based on previously detected symbols. This loop includes, on the one hand, a combiner of detected symbols, called the feedback combiner 420, at the output of the decision module 216, and on the other hand, a subtractor 440 between the direct combiner 400 and the feedback combiner 420.

[0072] The return combiner 420 is configured to provide, for each symbol period Ts, a linear combination of the symbols SH.A_|, S„_A_2, • • • previously detected by the decision module 216 A symbol periods earlier. This linear combination of symbols is denoted s'n.

[0073] For example, the return combiner 420 is a return filter, preferably a finite impulse response (FIR) digital filter. Alternatively, the return filter could be an infinite impulse response (IIR) filter.

[0074] The equalizer 210 further includes a configuration module 420a for the return combiner 420 designed to configure the latter according to parameters specific to the propagation channel 106, such as the channel matrix H, and configuration parameters of the forward combiner 400, such as the p H coefficients.

[0075] In the case where the return filter is a FIR filter, the configuration module 420a of the return combiner 420 of symbols determines a vector of coefficients q H defining the filter, this vector comprising Nb coefficients, so that the return filter 420 provides a linear combination of samples every Ts seconds.

[0076] The subtractor 440 is configured to calculate a difference d between the linear combination y'n of the samples yn and the linear combination of the previously detected symbols s'n, i.e., the difference d = y'n - s'n -

[0077] The equalizer 210 further includes an addition module 460 between the subtractor 440 and the decision module 216. Advantageously, the addition module 460 is configured to add a non-zero scalar component 0 to the difference d, so that the estimated zn is given by zn = y'- s'n + 0.

[0078] The addition of this non-zero scalar component 0 makes it possible to compensate at least in part for the bias resulting from the impact of the expectation E[s„] of the emitted symbols sn through the combined action of the channel matrix H and the coefficients p H.

[0079] The equalizer 210 further includes a configuration module 460a designed to calculate the non-zero scalar component 0 and to provide this component to the addition module 460 so as to add it to the difference d.

[0080] For example, the configuration module 460a is configured to calculate the non-zero scalar component 0 as a function of parameters related to the alphabet Q, such as the expectation E [ ] of the transmitted symbols sn, of configuration parameters of the upstream combiner 300, such as the coefficients p H, and / or of parameters specific to the propagation channel 106, such as the channel matrix H.

[0081] Thus, in the case where the equalizer 210 implements an upstream FIR filter 300 defined by the coefficients p H and a return FIR filter 320 defined by the coefficients q H, the estimated zn provided as input to the decision module 216 is such that:

[0082] [Math.4] z^^x^-^x^ + É?

[0083] where / sH A ; denotes the vector grouping the Nb past decisions relating to sn — \ ^nA-Nb / to the symbols transmitted A+l periods symbols earlier.

[0084] The configuration modules 400a, 420a, 460a are designed to configure, respectively, the direct combiner 400, the return combiner 420, and the addition module 460 of the scalar component. These modules can be implemented in software form executed by a single information processing module, such as the one described below with reference to [Fig. 9].

[0085] With reference to [Fig.5], a method 500 for configuring the equalizer 210 will now be described, in the case where the upstream combiner 400 and the return combiner 420 are FIR filters as described with reference to [Fig.4].

[0086] During an initialization step E50, the receiver 104 receives a known reference message from the transmitter 102. The noise estimator 212 and the channel estimator 214 described previously with reference to [Fig.2] determine, from an analysis of this known message, respectively the variance of the noise ow2 and the channel matrix H and provide this information to equalizer 210.

[0087] During a sampling step E51, the sampler 208 samples the received signal r(t) corresponding to an unknown message e(t) transmitted by the transmitter 102, so as to provide a set of blocks of M successive samples for N received symbols. Thus, a block of M samples is provided every Ts seconds (symbol period) by the sampler 208.

[0088] By collecting the last NxM samples received (i.e., N blocks of M samples) in vector form, up to the time NTS+(M-1) Ts / M, the samples can to be written within the framework of the modeling presented as follows:

[0089] [Math.5] mW+I 0 0 0 0 hQ

[0090] H denoting the channel matrix, preferably equal to a block Toeplitz matrix describing the inter-symbol interference pattern specific to the propagation channel, sn being the vector of emitted symbols participating in the inter-symbol interference symbols present in the last NxM samples received, and wn is a vector of Gaussian noise, centered, with variance ow2 on each coordinate and independent of the emitted signal.

[0091] For example, the channel matrix includes two nuisance blocks, more particularly a lower zero triangular block and an upper zero triangular block.

[0092] During a calculation step E53, the configuration module 400a of the direct combiner 400 calculates the coefficients p H, the configuration module 420a of the return combiner 420 calculates the coefficients q H and the configuration module 460a of the addition module 460 calculates the non-zero scalar component 0.

[0093] For example, the parameters p H, q H , 0 of the equalizer 210 are calculated so as to minimize the cost function "mean squared error" (MSE: "Minimum Square Error" in English) between the estimated zn and the symbol sn A>where A denotes the delay in symbol restoration by the receiver, denoted:

[0094] [Math.6] J(pH, q"," ©) = E|z„- s , M p

[0095] Alternatively, the pH, qH, 0 parameters of the equalizer 210 are calculated so as to minimize a bit error rate (BER: "Bit Error Rate").

[0096] Advantageously, the delay A can be optimized. For example, it is possible to try several values ​​of the delay A (for example by scanning) to find the best one, i.e. the one minimizing the cost function J.

[0097] The result of this minimization calculation of the function J allows us to determine the parameters p H, q H , 0 of the equalizer 210 according to the following expressions:

[0098] [Math.7] p» = ) H h + '

[0099] qa = pBHJi

[0100] 0 = 8(^)(1-^+¾)

[0101] where ( :. i ) denotes the sum of the column values ​​of the matrix channel H ; = H(:, A + 1 ) denotes the column A+1 of the matrix channel H ; E(sn) denotes the expected value of the symbols emitted; o? denotes the variance of the symbols emitted; q;* denotes the coefficient of rank i in qff; I denotes the identity matrix; / Qa+IWVj with s=N+L-2-A-Nb ; and 0 denotes the zero matrix. J4= \ OjxATj /

[0102] Thus, the value of the non-zero scalar component 0 is defined in particular as a function of the mathematical expectation of the non-centered alphabet Q and of the channel matrix H modeling in particular the interferences between symbols.

[0103] This result is obtained by making the following assumptions: the value of the emitted symbols sn is a stationary random variable, so that the mathematical expectation of the symbols is invariant over time, i.e. E(s„) = E⇇s^); the noise is uncorrelated with the emitted symbols sn, so that the covariance of the noise and the symbols is zero; and the noise has a mathematical expectation of zero, i.e. E ( wn ) - 0.

[0104] The expressions calculated above are obtained assuming zero-mean Gaussian white noise. However, these can of course be adapted by a person skilled in the art to take into account other noise statistics, for example correlated noise, while remaining within the scope of the present invention.

[0105] The equations [Math 7] are for example determined beforehand and implemented respectively in the configuration modules 400a, 420a, 460a.

[0106] During a configuration step E55, the parameters p H, q H , 0 are applied respectively to the upstream filter 300, the return filter 320 and the addition module 360 ​​in order to configure the equalizer 210.

[0107] Once equalizer 210 is configured, the configuration parameters remain unchanged for the reception of multiple symbols.

[0108] With reference to [Fig.6], a second embodiment of the receiver according to the invention will now be described.

[0109] According to the second embodiment, the equalizer, which now bears the reference 610, differs from the equalizer 210 according to the first embodiment, in that it does not include a feedback loop.

[0110] Thus, the direct combiner 400 provides the linear combination yn from the samples yn and the addition module 460 adds to this linear combination yn the non-zero scalar component 0 so as to obtain the estimate zn, such that zn=yn + 0. In this way, the estimate zn is calculated independently of the previously detected Sn_A_0, ... symbols.

[0111] As described previously, the direct combiner 400 can be a FIR filter configured by the configuration module 400a, which is designed to calculate the p-H coefficients. Thus, the estimated zn is determined as a function of these coefficients, such that zn = pHx y n+0-

[0112] The process described with reference to [Fig.5] remains valid except that only the coefficients p H and the non-zero scalar component 0 are calculated during step E53.

[0113] The parameters p H and 0 of the equalizer 610 are calculated using the same assumptions as those previously applied to the first embodiment. In this case, the parameters of the equalizer 610 are determined according to the following expressions, with the same notation as before:

[0114] [Math.8] 0=E(^)(lp»E H )

[0115] It is observed that the non-zero scalar component 0 depends only on the predefined expectation of the alphabet Q, the channel matrix H and the coefficients p H.

[0116] Assuming that the value of the symbols sn is a stationary random variable, then the associated expectation is time-invariant, so that E(sn_A) = E(s„). Assuming that the propagation channel 106 is stationary over a reference period, the channel matrix H is time-invariant. In this case, the non-zero scalar component 0 is a constant over this reference period.

[0117] In both embodiments described above, the parameters of the equalizer 210 are initially calculated analytically, in particular as a function of external parameters related to the propagation channel 106, noise, and the statistical properties of the symbols sn. In particular, the channel estimator 214 and The noise estimator 212 can be used to provide the equalizer 210 with the channel matrix H and the noise variance ow2.

[0118] Alternatively, the parameters (0, p H, q H) or (0, p H) of the equalizer 210 can be determined adaptively by a convergence and tracking technique. This technique constitutes a variant embodiment that can be applied to each of the embodiments described above.

[0119] With reference to [Fig.7], a variant of the first embodiment of the equalizer will now be described for determining and adjusting the parameters of the equalizer according to a convergence and tracking technique.

[0120] According to this variant, the equalizer, now designated 710, is designed to iteratively update the scalar component 0 based on symbols previously determined by the decision module 216. This does not require the use of a decoder (a "soft demapper") that uses several successive estimates to analyze them as with error correction. On the contrary, the decision module 216 provides each symbol $A from a single estimate zn.

[0121] Thus, the equalizer 710 further includes a comparison module 780 of the symbols previously detected by the decision module 216 at the estimated zn, so as to calculate an error signal en. For example, the error signal en provided at the output of the comparison module 780 is such that e« ~ z«~La.

[0122] The comparator module 780 has an output connected to the configuration module 700a of the direct combiner 400, to the configuration module 720a of the return combiner 420 and to the configuration module 760a of the add module 460, so that the error signal is provided, for each symbol period, simultaneously at the input of these configuration modules 700a, 720a, 760a.

[0123] A method 800 for configuring the equalizer 710 will now be described in more detail with reference to [Fig.7].

[0124] During an initialization step E80, the parameters p H , q H , 0 of the equalizer 710 are initialized, for example with the following default values: p H=( 1,0,0,.. .,0) ; q H=(0,0,0,...,0) ;0=0.

[0125] During an E82 transmit / receive step, the transmitter 102 starts sending a known symbol sequence and the receiver 104 receives this sequence.

[0126] This known symbol sequence is used by the equalizer 710 to update its configuration parameters p H , q H , 0 , as it receives symbols from the known sequence. This update is performed iteratively, during a convergence phase B1 as detailed below.

[0127] For each new set of M samples yn provided by the sampler 208, the configuration parameters p H , q H, 0 of the equalizer 710 are updated. Thus, The parameters of the 710 equalizer are updated once per symbol period, for each known symbol of the sequence, received during the convergence phase Bl.

[0128] This update is carried out by comparing the estimated zn of the symbols to the symbols of the known sequence.

[0129] Each symbol sn of the known sequence is received by the receiver with a delay A. Thus, during a comparison step E84, the comparison module 780 provides, for each symbol period, the error signal e(n) between the estimated zn and the received symbol sn A such that e" = This error signal e(n) is transmitted at each symbol period to the configuration modules 700a, 720a, 760a.

[0130] During an update step E86, the configuration modules 700a, 720a, 760a calculate the configuration parameters p H, q H, 0 of the equalizer 710 as a function of the initial value set during the initialization step E80 or of a previous value of the parameters determined during the previous period (i.e. during a previous iteration).

[0131] For example, during the E86 update step, • The 700a configuration module of the upstream filter 400 is configured to calculate the p H coefficients of said filter according to the following recurrence formula: [Math.9] • The 720a configuration module of the 420 return filter is configured to calculate the q H coefficients of said filter according to the following recurrence formula: [Math. 10] UUA fi • The configuration module 760a of the add-in module 460 is configured to calculate the scalar component 0 according to the following recurrence formula: [Math. 11]

[0132] where ~ z"- -La denotes the difference (or error) between the estimated zn and the symbol sn A emitted with a delay A for the symbol period Tn; qi denotes an adaptation step, preferably less than 1, for the adaptation of the coefficients p H of the upstream filter and the coefficients q H of the return filter and q2 denotes an adaptation step, preferably less than 1, for the adaptation of the scalar component 0. For example, the adaptation steps qietq2sonte equal, so that qi=q2.

[0133] This update is performed iteratively, i.e., period by period, so as to converge towards a target value. Thus, after each update, the equalizer 710 determines, during a test step E88, whether a convergence criterion has been met. For example, a convergence criterion is such that the difference is less than a predetermined convergence threshold eb

[0134] As soon as the error is less than the predetermined convergence threshold eb (i.e., e(n) <ei) une phase de poursuite B2 est mise en œuvre qui va être décrite ci-dessous plus en détails.

[0135] During this tracking phase B2, the updating of the equalizer 710 parameters is driven by previous symbol detections. Thus, the tracking step B2 differs from the convergence step B1 in that it uses the detected symbols s A in the error en instead of the emitted symbols sn A to update the equalizer 710 parameters.

[0136] Thus, during a step E89, the error signal e(n) is replaced by an error signal between the estimated zn and the symbol s„ , detected with a delay A so that e„ — z„-s t.

[0137] The parameters of the equalizer 710 are determined at each iteration during the update step E86, by the same equations Math 9, Math 10 and Math 11 as described previously, as long as the error in — zn - sn_^ is greater than the predetermined convergence threshold eb

[0138] As soon as this error e(n) becomes greater than the predetermined convergence threshold eb the process switches to the convergence phase B1 by executing steps E84, E86 as long as en>ei as described previously.

[0139] With reference to [Fig.9], a variant of the second embodiment of the equalizer will now be described for determining and adjusting the parameters of the equalizer according to the convergence and tracking technique previously described.

[0140] According to this variant, the equalizer, which now bears the reference 910, is designed to iteratively determine its configuration parameter 0, p H.

[0141] As described with reference to [Fig. 7], the equalizer 910 includes the comparison module 780 of the symbols previously detected by the decision module 216 at the estimated zn, so as to calculate the error signal en. As described previously, the configuration parameters 0, p H of the equalizer 910 are updated at each iteration as a function of the error signal e(n), respectively by the configuration modules 900a and 960a according to the same process 800 as described with reference to [Fig. 8] with the difference that only the parameters 0, p H .

[0142] For example, during the E86 update step, • the 900a configuration module of the upstream filter 400 is configured to calculate the p H coefficients of said filter according to the recurrence formula [Math 9]; • The configuration module 960a of the addition module 460 is configured to calculate the scalar component 0 according to the recurrence formula [Math 11].

[0143] In the examples described above, the receiver 106 according to the invention may include a computer system 10, as illustrated in the form of a block diagram in [Fig. 10], adapted for the implementation of one or more modules described above.

[0144] This computer system 10 comprises a data processing unit 10.1 (such as a microprocessor, denoted CPU, from the English "Central Processing Unit"), a main memory 10.2 (such as random access memory, denoted RAM, from the English "Random Access Memory") accessible by the processing unit 10.1, a read-only memory 10.3, denoted ROM, from the English "Read Only Memory"), accessible by the processing unit 10.1, an optional computer-readable storage medium, such as, for example, local storage (such as a local hard drive 10.6, denoted HD, from the English "Hard Drive") or removable storage (such as a USB flash drive, from the English "Universal Serial Bus", or a CD, from the English "Compact Disc", or a DVD, from the English "Digital Versatile Disc") readable by means of a suitable reader of the computer system 10 (such as that a USB port or a CD and / or DVD disc drive); an input / output module 10.7 for receiving / sending data from / to external devices such as hard drives, removable storage media or others.

[0145] A computer program P containing instructions in the form of executable code for the processing unit 10.1 is recorded on the medium 10.6.

[0146] This computer program P is, for example, intended to be loaded into main memory so that the processing unit 10.1 can execute its instructions. These instructions implement one or more of the modules described above, which are thus software modules.

[0147] Alternatively, all or part of these modules could be implemented as hardware modules, i.e. in the form of an electronic circuit, for example micro-wired, not involving a computer program.

[0148] It is clear that a receiver such as the one described above makes it possible, by adding a non-zero scalar component in the estimate zn before symbol detection, to improve the performance of symbol detection.

[0149] It should also be noted that the invention is not limited to the embodiments described above. It will indeed be apparent to those skilled in the art that various Modifications may be made to the embodiments described above, in light of the teaching which has just been disclosed to him.

[0150] The above embodiments and variants have been described to improve the detection performance of a digital data receiver in the presence of inter-symbol interference, which is the most frequent use case. More generally, the invention can also be applied to any other type of distortion or interference caused by the propagation channel, insofar as these can be modeled in the form of a compatible Toeplitz matrix so that the sampled signal yn can be written in the matrix form yn=Hs n+wn according to the expression [Math 5].

[0151] In the examples described above, finite impulse response filters have been described to implement the sample combiner (i.e., forward filter) and the combiner of previously detected symbols (i.e., return filter). Other types of filters may also be used.

[0152] In the detailed presentation of the invention given above, the terms used shall not be interpreted as limiting the invention to the embodiments set forth in this description, but shall be interpreted as including all equivalents which can be foreseen by a person skilled in the art by applying their general knowledge to the implementation of the teaching which has just been disclosed to them.

Claims

Claims

1. Digital data receiver (104) comprising: - a sampler (208) designed to sample a received signal (r(t)) having propagated in a propagation channel (106), N successive symbols (sn) being encoded in this received signal (r(t)), in order to provide a set of blocks of samples for the N symbols (sn) received, the symbols (sn) belonging to a predefined alphabet (Q), the sampler (208) providing N blocks of M samples, M being at least equal to 1; - an equalizer (210; 610; 710; 910) designed to calculate, for each symbol (sn) received, an estimate (zn) of this received symbol (sn) from the samples provided by the sampler (208), the equalizer comprising a sample combiner (400) designed to receive said samples provided by the sampler and provide a linear combination of said samples, said estimate of a received symbol being determined from the linear combination;and - a decision module (216) designed to determine the symbol of the alphabet (Q) closest to the estimate (zn) as the detected symbol (¾); characterized in that the alphabet (Q) has an offset so that the emitted symbols (sn) have a predefined expectation (E[s„]) that is not zero, and in that the equalizer (210; 610; 710; 910) is designed to add a non-zero scalar component (0) to the linear combination to at least partially compensate for the offset; the equalizer (710; 910) being designed to iteratively update (E86) (B1, B2) the scalar component (0) as a function of symbols previously determined by the decision module (216).;

2. Receiver according to claim 1, wherein the equalizer (210; 610) is adapted to calculate the scalar component (0) from coefficients (p H) of the linear combination of the samples and the predefined expectation (E [sn ] ).

3. Receiver according to claim 2, wherein the equalizer (210; 610) is adapted to calculate the scalar component (0) from a channel matrix (H) representative of the propagation channel (106).

4. A receiver according to claim 3, wherein said channel matrix (H) is a block Toeplitz matrix.

5. Receiver according to any one of claims 1 to 4, wherein the equalizer (210; 610) is adapted to calculate said scalar component (0) in order to minimize a mean square error between the transmitted symbols (sn) and the estimated ones (zn).

6. Receiver according to any one of claims 1 to 5, wherein the equalizer (210;610;710;910) comprises a direct filter (400), preferably with finite impulse response, and the equalizer is adapted to apply this direct filter (400) to the samples to provide said linear combination.

7. Receiver according to any one of claims 1 to 6, in which the equalizer (610) is designed to calculate, for each symbol (sn) received, the estimate (zn) of this symbol (sn) independently of previously detected symbols.

8. Receiver according to any one of claims 1 to 6, in which the equalizer (210; 710) is designed to calculate, for each symbol (sn) received, the estimate (zn) of this symbol (sn) from a difference (d) between the linear combination of the samples for this symbol (sn) and a linear combination (s') of previously detected symbols (^ the scalar component (0) being added to this difference (d).

9. Receiver according to claim 8, in which the equalizer (210; 710) further comprises a so-called feedback filter (420), preferably with finite impulse response, and the equalizer (210; 710) is designed to apply this feedback filter (420) to the previously detected symbols ( è £ ] so as to provide said linear combination (s') of previously detected symbols (J

10. A receiver according to claim 6, wherein the equalizer (210; 610; 710; 910) is arranged to calculate the scalar component (0) from the direct filter (400).

11. Receiver according to claims 9 and 10, wherein the equalizer (210; 710) is arranged to calculate the scalar component (0) further from the feedback filter (420).

12. Receiver according to any one of claims 1 to 11, wherein the equalizer (710; 910) is configured to calculate the scalar component (0) according to the following recurrence formula: [Math. 12] where e" denotes the error signal defined by the difference between the estimate zn and the symbol sn A transmitted with a delay A for a symbol period Tn; (12 denotes an adaptation step, preferably less than 1, for the adaptation of the scalar component 0.

13. Digital communication system (100) characterized in that it comprises a transmitter (102) designed to transmit symbols selected from an alphabet (Q) of non-zero expectation, and a receiver (104) according to any one of claims 1 to 12.

14. A method for receiving digital data, comprising: - sampling a received signal (r(t)) having propagated in a propagation channel, N successive symbols (sn) being encoded in this received signal (r(t)), in order to provide a set of blocks of samples for the N symbols (sn) received, the symbols (sn) belonging to a predefined alphabet (Q), the sampling step providing N blocks of M samples, M being at least equal to 1; - linear equalization by calculating, for each symbol (sn) received, an estimate (zn) of this received symbol (sn) from the samples provided by the sampling step, the equalization step comprising a linear combination (400) of the samples provided by the sampling step, said estimate of a received symbol being determined from the linear combination; and - a determination of the symbol of the alphabet (Q) closest to the estimate (zn) as detected symbol (s„);characterized in that the alphabet (Q) has an offset so that the emitted symbols (sn) have a predefined expectation (E[s„]) which is not zero, in that the linear equalization comprises an addition of a non-zero scalar component (0) to the linear combination to at least partly compensate for the offset, the scalar component; 22 (0) being updated iteratively (Bl, B2) according to symbols previously determined by the decision module (216).

15. Computer program (P) downloadable from a communication network and / or recorded on a computer-readable medium, characterized in that it comprises instructions for executing the steps of a method according to claim 14, when said program (P) is executed on a computer.

Images