Methods, devices and programs for demodulating a data frame

Abstract

The invention relates to a method for demodulating a data frame comprising N information words in which a word occupying a position in the frame is modulated by a symbol from a dictionary of symbols, the method comprising the steps of determining (301), for a plurality of symbols and the frame, with , a vector of K probabilities , called relative distribution, , comprising probabilities associated with K possible values ​​of an estimated difference between the symbols and , of combining (303) a relative distribution with a particular probability distribution determined (302) according to a characteristic of the channel, and of demodulating (304) the frame from at least a part of the combined distributions. Abstract figure: Figure 3.

Description

Title of the invention: Methods, devices and programs for demodulating a data frame Technical field

[0001] The invention generally belongs to the field of telecommunications and more particularly relates to a modulation technique making it possible to improve the demodulation performance of a data frame, in particular in communication systems which rely on a relative representation of the information for the purpose of its transmission and / or its processing. Prior art

[0002] Communication systems are known that rely on a relative representation of information for the purpose of its transmission and / or processing. A common example is the use of differential modulations.

[0003] Consider for example a frame of 5 symbols [xq, _x15 x2, Xy x4], each encoding k bits of information, and thus able to take 2^ values. A possible differential representation of the frame can be [x0 / i, x1 / 2, x2 / 3, X3 / 4 ] “ [x0- x{, x}-x2, x2-X4-X3]. In this example, it is therefore the difference between the values ​​that is coded, and a single absolute reference is sufficient to decode the complete frame. Of course, in such a configuration, the subtraction, or any other operation, is done in the finite field considered, here F^ (i.e. modulo k).

[0004] Such a representation can be used for signal transmission or processing purposes within the communication chain. For example, when the variations between consecutive samples are small, transmitting differences between samples can be particularly effective.

[0005] Such a differential representation of the frame may also prove useful in certain receivers, for example when receiving a signal modulated by the cyclic rotation of a root sequence of complex symbols, such as a CCSK modulation (for Cyclic Code-Shift Keying in English).

[0006] CCSK modulation proposes to modulate the data to be transmitted by the cyclic rotation / shift of a sequence of complex symbols called the root sequence. The root sequence is such that its shifted versions are orthogonal to each other, that is to say that it offers a good autocorrelation function. Thus, each binary word to be transmitted is associated with a particular cyclic shift of the same root sequence.

[0007] For example, by choosing a root sequence composed of the 4 symbols complex [a; b; c; d], CCSK modulation allows 2 bits of information to be modulated orthogonally via the rotations of this sequence. The binary word '00' can correspond to the transmission of the sequence [a; b; c; d]; the binary word '01' may correspond to the transmission of the sequence [d; a; b; c]; the binary word '10' may correspond to the transmission of the sequence [c; d; a; b], etc.

[0008] The CCSK sequences can advantageously be transmitted in a CP-OFDM frame (for Cylic Prefix Orthogonal Frequency Division Multiplex in English), for example in a time-frequency frame in which each of the N time steps contains a complete CCSK sequence of size K distributed over all the frequency subcarriers as shown in [Fig. 1].

[0009] Knowledge by the receiver of the absolute offset of a particular sequence of the frame allows the demodulation of the entire frame. For example, when the offset of the first sequence is known, for example when a particular sequence is present at the start of the frame by convention, the receiver can demodulate the frame by estimating the offsets of the other sequences relative to the known sequence.

[0010] It is thus necessary to have a good knowledge of the differences between the sequences of the same frame in order to correctly demodulate the data. However, it happens that disturbances do not affect the symbols transmitted in the same frame in the same way, which can cause problems during its demodulation. Indeed, in certain circumstances, the communication system can undergo variations in the communication channel over time. This is for example the case in the presence of a Doppler effect due to a relative displacement between the receiver and the transmitter. This evolution of the channel is all the more rapid as the relative transmitter-receiver speed is high. A typical example is the case of satellite communications, in which the relative speeds considered can be particularly high.

[0011] There is therefore a need for a method which makes it possible to improve the demodulation performance when the channel is subject to disturbances affecting the symbols of the same frame differently, for example when these disturbances vary over time, in particular when the communication is based on a relative representation of the information. Summary of the invention

[0012] For this purpose, a method is proposed for demodulating a data frame comprising N information words D ] in which a word P; occupying an E0 "1N-1J position i G [0, N - 1] in the frame is modulated by a symbol Cpj from a dictionary of K symbols, the method comprising the following steps: - Determination, for a plurality of symbols CPi c{CP; of the frame, with i, j E [ 0, N - 1], of a vector of K probabilities called relative distribution, comprising probabilities respectively associated with K possible values ​​of an estimated difference between the symbols CPj and Cpp - Combination of a relative distribution Pj / j with a particular probability distribution mask^y determined according to a characteristic of the communication channel, - Demodulation of the frame from at least part of the combined distributions.

[0013] The operation of difference between symbols discussed in this document depends on the modulation technique used. In the case of CCSK modulation, such a difference corresponds for example to the value of a cyclic shift of the sequence considered with respect to another sequence. In the case of QPSK modulation, the difference operator is adapted to estimate phase or angle shifts. The difference between symbols can also correspond to a difference between index values ​​associated with the symbols in a symbol dictionary, according to an indexing system equal to the set {0, 1, ..., Kl] up to an isomorphism, and their respective probabilities. The difference is thus estimated in a finite group of size K, that is to say modulo the cardinality of the symbol dictionary when an indexing in the form {0, 1, ..., Kl} is assumed.

[0014] We recall here that a group, in the mathematical sense of the term, is a set provided with a unique internal composition law which is associative, possessing a neutral element. A finite group is a group whose number of elements is finite.

[0015] A relative distribution P^j represents a probability of the relative value of the symbol CPi with respect to the symbol Cpf, knowing the channel estimated using the symbol Cpj (and vice versa). Thus, when the channel varies over time, for example in the presence of Doppler, and the distributions P are affected by the correlation between the channels undergone by Cpj and Cpp then for values ​​of / and j distant in the OFDM frame, these distributions are not necessarily reliable.

[0016] According to another example, when considering time-constant channels and several spatial layers, for example in a MIMO (Multiple Input Multiple Output) system using spatial multiplexing, the level of channel correlation between different layers can affect the estimation of a difference between symbols. For example, in a system using 4 spatial layers, one can have layer 1 and 4 slightly correlated and layer 1 and 2 and 1 and 3 completely decorrelated. The determination and application of a suitable mask makes it possible to limit the influence of unreliable Pj / j distributions.

[0017]

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] The method thus proposes to combine probability distributions of a difference between symbols of the frame with masking distributions which are determined according to a characteristic of the channel on which a level of confidence in the estimation of the symbols or the differences of the symbols depends, so as to adjust the effect of certain probability distributions on the demodulation process. The relative distributions thus filtered, representative of probabilities of difference between symbols, are used to demodulate the information words of the frame. For example, when a symbol of the frame is known to the receiver, such as a pilot symbol, knowledge of the differences between the symbols allows the demodulation of the complete frame. The method makes it possible to give variable importance to the distributions representative of these differences according to their reliability. The demodulation performance is thus improved. According to a particular embodiment, the demodulation of the frame is carried out at from at least one partial relative distribution determined by relating of a first combined relative distribution determined from symbols CPi and CPm with a second combined relative distribution determined from a symbol Cpj and the symbol CPm, with i, j ï m, and m G [0; N -1], It is thus proposed to determine so-called partial relative distributions from masked relative distributions determined for symbols CPl and CPm on the one hand, and on the other hand from combined relative distributions determined for the symbols Cpj and CPm. In other words, we determine a difference between a first symbol and a second symbol by transitivity, that is, from a difference between the first symbol and a third symbol and an index difference between the second symbol and the same third symbol. This gives a plurality of estimates of the index difference between the first and second symbols based on different symbols. The partial relative distributions determined for a particular m-value are then combined by product to obtain a consolidated version of a relative distribution in which the distributions deemed unreliable have little influence. In a particular embodiment, a particular probability distribution mask^y is determined according to a reliability level determined for the symbols CPi and Cpj and / or a reliability level determined for the difference between these symbols. Masking distributions are for example determined according to the reliability of symbol estimation and / or the reliability in estimating a symbol gap. In this way, it is possible to determine a masking distribution by particular which is configured to limit the influence of unreliable estimates and / or give more importance in a combined distribution to the most reliable symbols and / or differences between symbols.

[0024] According to a particular embodiment, a relative distribution P^- is convolved with a Kronecker distribution with a peak at 0 (denoted Kronecker[0]) when the number of symbols which separate symbols CPi and CPj in the frame is less than a threshold, and with a uniform distribution when this number is greater than or equal to said threshold, the threshold being determined according to a characteristic of the communication channel.

[0025] In this way, the differences between symbols that are distant in the frame are not taken into account for the demodulation process. In the presence of a Doppler effect for example, the symbols at the start of the frame and at the end of the frame do not undergo the same channel because the latter varies over time. In this way, the method avoids introducing these unreliable estimates into the demodulation process. The threshold from which the relative distributions are suppressed is defined according to a characteristic of the communication channel.

[0026] According to a particular embodiment, a relative distribution P-^ is convolved with a probability distribution mask^; intermediate between a Kronecker distribution [0] and a uniform distribution U such that maskÿy = a^Ô[0] + ( 1- a^) the parameter being determined according to a characteristic of the communication channel.

[0027] Such an arrangement makes it possible to finely adjust the level of consideration of a particular distribution P^j during the demodulation step, according to the degree of confidence that one wishes to grant it.

[0028] According to a particular embodiment, a probability distribution mask^y is determined according to the number of symbols separating the symbols CPi and Cpj in the frame and a level of temporal variability of the channel.

[0029] When the channel is subject to temporal variations, for example in the case of a Doppler effect, the symbols at the start and end of the frame are not affected in the same way, so that an estimated difference between these symbols may prove to be unreliable. By determining a mask which takes into account both the distance separating pairs of symbols in the frame and a level of temporal variability of the channel, for example a Doppler level, it is possible to discard the least relevant probability distributions and thus improve the demodulation performance.

[0030] According to a particular embodiment, the method is such that a symbol CPi is a sequence of complex values ​​obtained by applying a cyclic shift by-

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037] particular to a root sequence of size a CPi sequence being received on K subcarriers of an OFDM symbol. The information to be transmitted is modulated by a cyclic shift of a root sequence known to the receiver. This is, for example, a CCSK-type modulation using a Zadoff-Chu-type root sequence. CCSK sequences (or symbols) are integrated into a CP-OFDM frame so that each element composing a CCSK sequence, called a chip, is transmitted on a separate OFDM subcarrier. In its simplest form, we then obtain a time-frequency frame in which each of the N time steps contains a complete CCSK symbol of size K distributed over all the subcarriers in frequency, as shown in [Fig.l]. Since the root sequence (and therefore all its cyclic shifts) are known to the receiver, the transmitted CCSK sequences can then serve as pilot sequences for synchronization and channel estimation, while carrying information. The calculated differences can thus correspond to differences between indexes associated with the symbols or differences between the offsets of the sequences composing the symbols. According to another aspect, the invention relates to a device for demodulating a data frame comprising a sequence of information words p J in which a word Pi occupying a position i G [0, N - 1] in the frame is modulated by a symbol Cpi from a dictionary of K symbols, the device comprising a processor coupled to a memory in which program instructions are recorded configured to implement the following steps: - Determination, for a plurality of CPi and Cpj symbols of the frame, with i, j G [ 0. N - 1], of a vector of K probabilities P called relative distribution, comprising probabilities respectively associated with K possible values ​​of an estimated difference between the symbols CPi and Cpr - Combination of a relative distribution Pjjj with a particular probability distribution mask^j determined according to a characteristic of the communication channel - Demodulation of the frame from at least part of the combined distributions. The invention also relates to a communication terminal comprising a demodulation device as described above. In a particular embodiment, the different steps of the demodulation method are determined by computer program instructions.

[0038] Consequently, the invention also relates to a computer program comprising instructions adapted to the implementation of the steps of a demodulation method as described above, when the program is executed by a processor.

[0039] This program may use any programming language, and be in the form of source code, object code, or code intermediate between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0040] The invention also relates to a computer-readable information medium on which is recorded a computer program comprising instructions for executing the steps of a demodulation method as described above.

[0041] The information medium may be any entity or device capable of storing the program. For example, the medium may comprise a storage means, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, a flash memory, or a magnetic recording means, such as a hard disk.

[0042] On the other hand, the information medium may be a transmissible medium such as an electrical or optical signal, which may be conveyed via an electrical or optical cable, by radio or by other means. The program according to the invention may in particular be downloaded from an Internet-type network.

[0043] Alternatively, the information carrier may be an integrated circuit in which the program is incorporated, the circuit being adapted to execute or to be used in the execution of the method in question.

[0044] The various embodiments or features mentioned above may be added independently or in combination with each other, to the steps of the demodulation method.

[0045] The devices, terminals, programs and information media have advantages similar to those conferred by the method to which they correspond. Brief description of the figures

[0046] Other characteristics and advantages will appear on reading a preferred embodiment described with reference to the appended drawings among which: - [Fig.l] represents an environment suitable for implementing the demodulation method according to a particular embodiment, - [Fig.2] illustrates a time-frequency frame in which each of the N time steps contains a complete symbol of size K distributed over all the subcarriers in frequency, - [Fig.3] is a flowchart representing the main stages of a demodulation process according to a particular implementation, - [Fig.4a] is a graph showing an example of relative distribution, - [Fig.4b] represents a graph showing a distribution of Kronecker[0], - [Fig.4c] is a graph illustrating a relative distribution resulting from the convolution of the distributions represented in Figures 4a and 4b, according to a particular embodiment, - [Fig.5a] is a graph showing an example of relative distribution, - [Fig.5b] represents a graph showing a uniform distribution, - [Fig.5c] is a graph illustrating a relative distribution resulting from the convolution of the distributions represented in figures 5a and 5b, according to a particular embodiment, - [Fig.6a] is a graph showing an example of relative distribution, - [Fig.6b] represents a graph showing a masking distribution intermediate between a Kronecker distribution[0] and a uniform distribution, - [Fig.6c] is a graph illustrating a relative distribution resulting from the convolution of the distributions represented in Figures 6a and 6b, according to a particular embodiment, and - [Fig.7] is a block diagram representing the architecture of a device suitable for implementing the demodulation method in a particular embodiment. Detailed description

[0047] In the following description, embodiments are described on the basis of non-limiting examples making it possible to explain the concepts on which the invention is based. In particular, although the examples and the terminology used may refer to certain well-known technologies or standards, these references are not limiting and other technologies may be adapted to implement the concepts of the invention. For example, the CCSK modulation technique referred to may be replaced by other modulation techniques, such as QPSK (Quadrature Phase Shift Keying), or QAM (Quadrature Amplitude Modulation), without it being necessary to modify the invention.

[0048] [Fig. 1] represents an environment suitable for implementing the demodulation method according to a particular embodiment.

[0049] The environment comprises a communication system 100, comprising a transmission device 101 and a reception device 102. The transmission device 101 is for example a communication terminal, a piece of equipment used liseur (UE, for User Equipment in English), a base station, a connected object, a telecommunications satellite, etc. The receiving device 101, for example user equipment, a terminal, a vehicle or a connected object, or any other device adapted to receive wireless data.

[0050] The devices 101 and 102 comprise radio frequency communication means, for example a transceiver adapted to allow the devices 101 and 102 to communicate by exchanging time-frequency data frames, for example CP-OFDM frames.

[0051] In a particular embodiment, such frames comprise a plurality of information words, for example binary words of size P bits, which are modulated by a CCSK symbol, i.e. by a particular sequence of complex values ​​obtained by cyclic shift of a root sequence of size 2'r, which has a good autocorrelation function. Such a sequence, for example a Zadof-Chu sequence.

[0052] Thus, the communication system 100 implements a CCSK-CP-OFDM modulation. The CCSK-CP-OFDM approach combines the CP-OFDM technique with the CCSK modulation with the aim of achieving small packet communications for the IoT, with high energy efficiency. It may however be noted that other modulation techniques may be envisaged without modifying the invention, as indicated above.

[0053] Figure 2 represents an example of a CCSK-CP-OFDM frame in which each of the N time steps contains a complete CCSK sequence of size K = 2P distributed over all K frequency subcarriers, so that each symbol can code a word of size P bits.

[0054] The set of K CCSK sequences constitutes a dictionary of symbols of cardinality K.

[0055] In a particular embodiment, each symbol of the dictionary is associated with a distinct index so that the K symbols of the dictionary are respectively associated with K index values. In the case of CCSK modulation, each CCSK sequence of the dictionary can thus be associated with a unique digital value representative of the offset of the sequence relative to the root sequence.

[0056] According to a particular embodiment, the K index values ​​with which the symbols of the dictionary are associated constitute a finite group H of size provided with an addition law admitting 0 as a neutral element, so that each symbol of the dictionary is associated with a distinct value belonging to the finite group H.

[0057] The operations on the indexes, in particular the sums and differences, are thus carried out modulo the cardinality K of the symbol dictionary when we assume an indexing in the form {0, 1, ..., Kl], so that any difference (or sum) modulo K between elements of the set is also a value belonging to the set.

[0058] In a particular embodiment, the index values ​​are defined by the group mZ, / mKZ, considering a modular arithmetic on the remainders of the division by mK andm a strictly positive integer, Z being the set of relative integers.

[0059] For example, with m - 2 and K = 4, we obtain a set of indexes [0, 2, 4, 6] such that any difference (or sum) modulo mK between elements of the set is also a value belonging to the set. Thus, in this example, we actually observe that 0 - 2 = -2 [8] = 6, 0 - 4 = -4 [8] = 4, 2 - 4 = -2 [8] = 6, etc...

[0060] A particular embodiment of the demodulation method will now be described with reference to [Fig. 3]. The method is for example implemented by the device 102 of [Fig. 1].

[0061] During a first step 300, the device 102 receives a CCSK-CP-OFDM data frame comprising N information words [Po .. PAr J in which a word P, occupying a position i E [0, N - 1] in the frame is modulated by a CCSK sequence Cpi from a dictionary of K sequences

[0062] In step 301, the device 102 determines so-called relative symbol distributions from the symbol distributions determined in step 301.

[0063] A relative distribution represents probabilities of differences between pairs of symbols received in the frame. These relative distributions are determined for all pairs of symbols (Cpi, Cpj) of the frame, f, j E [ 0, N - 1 ], by operations of cross-correlation or convolution. More precisely, a difference between a symbol Cpj and a symbol Cpj is determined by relating these symbols by cross-correlation or convolution. This difference corresponds for example to the value of an offset between two CCSK sequences of the frame. Thus, for each pair of symbols {Cpj, Cp^ we determine a vector Pjfj whose size is equal to the cardinality K of the symbol dictionary, and each element Py of which includes a probability that the relative offset between the symbols Cp[ and Cpj is of value 11.

[0064] These relative distributions make it possible to obtain a matrix of relative distributions in which an element of coordinates (i, j) is a relative distribution Pj[i:

[0065] Po / o ■■■ ^-1 / 0 ' P = ! : .^0 / Nl Pn-1!N-1.

[0066] According to a particular embodiment, the K symbols of the dictionary are associated with K distinct index values ​​of a finite group of order K, so that the differences between the symbols are expressed by differences between the indexes which are assigned to them. partners.

[0067] The method comprises a step 302 of determining a masking matrix of dimensions in which an element j G [0, N - 1] is a Kronecker distribution [0], a uniform Kronecker distribution U or an intermediate distribution between a Kronecker distribution and a uniform distribution, a particular distribution being selected according to a reliability level granted to the difference between the symbols CPi and Cp] in the frame. For example, the device 102 can obtain a transmission error rate associated with a symbol CPi and a transmission error rate associated with a symbol Cpp and determine a mask^y distribution according to the error rates obtained, such that the lower the error rate, the more the distribution resembles a Kronecker distribution [ 0], and the higher the error rate, the more the distribution resembles a uniform distribution.

[0068] According to a particular embodiment, each element ( j) i. j G [0, N - 1 ] of the masking matrix is ​​determined according to the relative position of the symbols CPi and Cpj in the frame and according to a level of temporal variability of the channel. Indeed, under certain conditions, in particular when the channel undergoes temporal variations (such as a Doppler effect), the reliability of the relative distribution can be inversely proportional to the spacing of the symbols CPi and CPj in the frame.

[0069] According to a particular embodiment, an element ( / ; j ) f, jg [ 0, N - 1 ] of the masking matrix is ​​a distribution maskÿj which is a Kronecker distribution [0] when the number of symbols which separate symbols CPi and CPj in the frame is less than a threshold, and a uniform distribution U when the difference is greater than or equal to said threshold, the threshold being determined according to a characteristic of the communication channel.

[0070] According to a particular embodiment, an element ij G [0, N- 1] of the masking matrix is ​​an intermediate distribution mask^ between the Kronecker distribution [0] and the uniform distribution U such that mask^ - jô[0] + ( 1-ailj) U the parameter ai / j being determined according to the number of symbols separating the symbols CPi and CPj in the frame, and / or according to a characteristic of the communication channel, such as a level of temporal variability of the channel.

[0071] Different characteristics of the communication channel can be taken into account to determine one or more masking distributions. This can be a level of temporal variability of the channel, but not only. For example, in the case of a MIMO system, some layers can be particularly correlated and other

[0072]

[0073]

[0074]

[0075]

[0076]

[0077] no, so that the symbols of a frame can be influenced differently by the channel. The masking distributions can thus be determined according to a level of correlation between the layers of a MIMO system. The method comprises a step 303 during which the matrix of relative distributions determined in step 301 is combined by convolution with a masking matrix determined in step 302. Thus, each relative distribution P^j is convolved with a masking distribution mask,yy so as to give more or less importance to the distribution P^j according to the reliability of the symbols CPi and Cpj, or a reliability associated with their difference. The method finally comprises a demodulation step 305 during which at least part of the relative distributions convolved in step 304 is used to estimate the value of a symbol from another taken as reference. For example, demodulation can be performed from the probabilities of differences between a symbol whose value and location in the frame are known, for example a pilot symbol, and the other symbols in the frame. Knowledge of a reference symbol and the probabilities of differences between this symbol and the other symbols in the frame makes it possible to estimate the value of these other symbols. In another example, the demodulation may consist of a shifted demodulation from the consolidated relative distributions. The shifted demodulation consists of demodulating the frame by taking an arbitrary symbol value as a reference and performing an integrity check on the information words thus obtained. If the integrity check does not validate the frame, a new demodulation is performed by taking another symbol value as a reference and a new integrity check is performed. These steps are repeated until the frame is validated by the integrity check. In a particular embodiment, the demodulation is carried out on the basis of recombinant relative distributions, obtained by relating at least a first relative distribution to which a mask has been applied, determined from symbols CPi and CPm with a second masked relative distribution, determined from a symbol Cp, and the symbol CPm, with i, jm, and m E [0; N - 1]. In other words, a difference between a first symbol and a second symbol is determined by transitivity, that is, from a difference between the first symbol and a third symbol and from an index difference between the second symbol and the same third symbol. We can thus obtain a plurality of relative distributions pM called partial, representing the difference between the first and the second symbol, but based on different symbols. The partial relative distributions determined for a particular m-value are then combined by product to obtain a consolidated version of a dis- relative contribution P^j on the basis of which the demodulation step takes place.

[0078] Figure 4a is a graph showing an example of relative distribution P^j — [0.23, 0.1, 0.34, 0.1, 0.23] representative of the probabilities of difference between symbols CPi and Cp, of a data frame for a symbol dictionary of cardinality K=5.

[0079] Figure 4b represents a graph showing a masking distribution mask^y = [1,0, 0, 0, 0], i.e. a Kronecker distribution [ 0]•

[0080] Figure 4c is a graph illustrating the result of the convolution of the P^j distribution of Figure 4a with the masking distribution of Figure 4b. The resulting distribution is thus identical to the original distribution of Figure 4a. In other words, the convolution by the Kronecker distribution [0] does not affect the distribution.

[0081] Figure 5a is a graph showing an example of relative distribution Py • = [0.23, 0.1, 0.34. 0.1, 0.23] representative of the probabilities of difference between symbols CPi and Cp, of a data frame for a symbol dictionary of cardinality K=5.

[0082] Figure 5b represents a graph showing a masking distribution maskyy = [1 / 5, 1 / 5, 1 / 5, 1 / 5, 1 / 5], i.e. a uniform distribution. Such a distribution is for example selected to mask relative distributions deemed unreliable.

[0083] Figure 5c is a graph illustrating the result of the convolution of the P^i distribution of [Fig.5a] with the masking distribution of [Fig.5b]. The resulting distribution is a uniform distribution whose effect on demodulation will be neutral.

[0084] Figure 6a is a graph showing an example of relative distribution ^ = ^0.231, 0.1, 0.34. 0.1, 0.23] representative of the probabilities of difference between symbols CPi and Cpj of a data frame for a symbol dictionary of cardinality K=5.

[0085] Figure 6b represents a graph showing a masking distribution maskyy = [0.6, 0.1, 0.1, 0.1, 0.1], which is an intermediate distribution between a Kronecker distribution [0] and a uniform distribution. Such a distribution is for example selected to mask relative distributions whose reliability is average.

[0086] Figure 6c is a graph illustrating the result of convolving the Pj / j distribution of [Fig.6a] with the intermediate masking distribution of [Fig.6b]. The resulting distribution is one that reduces the gap between low probabilities and high probabilities, so that the effect on demodulation is mitigated.

[0087] Although the method is described here with reference to discrete laws, the present proposal can be generalized to continuous laws, for example by approximating the continuous law by a discretized law, or by modeling the distributions by their parameters (for example the mean and the variance J as parameters of a normal law). It is then appropriate to express the relationship between the parameters of the relative distributions.

[0088] [Fig.7] represents a simplified architecture of a device 700 adapted to implement the demodulation method according to a particular embodiment.

[0089] The device 700 comprises a data processing module comprising a storage space 701, for example a memory (MEM), a processing unit 702, equipped for example with a microprocessor (PROC), and controlled by a computer program (PGR) 703 whose instructions are configured to implement the demodulation method as described previously in relation to [Fig.3].

[0090] At initialization, the code instructions of the computer program 703 are for example loaded into the memory 701 before being executed by the processor of the processing unit 702. The microprocessor of the processing unit 702 implements, according to the instructions of the computer program 703, the steps of the demodulation method described above with reference to [Fig.3].

[0091] For this, in addition to the memory 701 and the processor 702, the device comprises communication means 704, for example an OFDM transducer adapted to receive a signal on a plurality of orthogonal carriers. The communication means 704 are for example configured by computer program instructions to allow the reception of at least one time-frequency frame in which each of the N time steps contains a complete symbol of size K, for example a CCSK sequence, distributed over all the frequency subcarriers, and to demodulate the N OFDM symbols received.

[0092] The device 700 also comprises a module 705 for determining a matrix comprising a set of probability distributions, called relative distributions, each element P^j of the matrix being a vector of K probabilities representative of at least one difference between symbols CPi and Cpj of a plurality of pairs of symbols (CPi; Cpj) formed from the symbols composing a frame received by the communication means 704, with i E [0; N - 1] and je [ 0; N - 1], a difference being calculated according to modular arithmetic. The module 707 is for example implemented by computer program instructions configured to calculate a difference between index values ​​associated with two symbols of the frame by a cross-correlation and / or convolution operation and to store the result of the difference between the elements of a pair (CPi; Cpf) of sequences at coordinates (i: j) in the matrix.

[0093] The device 700 comprises a module 706 for determining a masking matrix comprising a set of distributions mask^y determined according to a reliability level of the symbols CPi and Cpj and / or a reliability level of the difference between these symbols. The module 706 can be implemented by program instructions configured to assign a Kronecker distribution [0] to the element at the coordinates (i; j) of the matrix when the number of symbols which separate symbols CPi and Cpj in the frame is less than a threshold, and a uniform distribution U when the difference is greater than or equal to said threshold, the threshold being determined by a level of temporal variability of the channel.According to a particular embodiment, the program instructions are configured to assign to the element (i; j) of the matrix an intermediate distribution between the Kronecker distribution [0] and the uniform distribution U such that mask^y = a^5[0] + ( 1- U> the parameter ailj being determined according to the number of symbols separating the symbols CPi and Cpj in the frame and a level of temporal variability of the channel.

[0094] The device 700 also comprises a module 707 for calculating a convolution of the matrix of relative distributions determined by the module 705 with the masking matrix determined by the module 706. The module can be implemented by program instructions configured to calculate such a convolution and produce a convolved relative distribution matrix in which the importance of the distributions is affected by the corresponding masking distributions.

[0095] The device 700 finally comprises a demodulation module 708 adapted to demodulate the symbols transmitted in the received frame from the relative distributions convolved by the module 707. For example, the module 708 is implemented by program instructions adapted to carry out an offset demodulation of the data frame based on the convolved relative offsets, for example from the offsets of one or more particular rows of the convolved matrix. According to another example, the instructions are configured to demodulate the symbols of the frame from the differences between these symbols and a reference symbol whose location and value are known.

[0096] In a particular embodiment, the device 700 is integrated into a communication terminal, a connected object, a vehicle, a gateway, an access point, a communication satellite or even a base station.

Claims

Claims

1. Method for demodulating a data frame comprising N information words n 1 in which a word Pi occupying a position PO " <v-il i G [0, N - 1] dans la trame est modulé par un symbole Cpi d’un dictionnaire de K symboles, le procédé comprenant les étapes suivantes : - Détermination (301), pour une pluralité de symboles CPi et Cpj de la trame, avec i, J G [ 0, N - 1], d’un vecteur de K probabilités P^j, dit distribution relative, comprenant des probabilités associées à K valeurs possibles d’une différence estimée entre les symboles CPi et Cpp - Combinaison (303) d’une distribution relative Pavec une distribution de probabilité particulière mask^- déterminée (302) selon une caractéristique du canal de communication, - Démodulation (304) de la trame à partir d’au moins une partie des distributions combinées.

2. Method according to claim 1 in which the demodulation of the frame is carried out from at least one partial relative distribution determined by relating a first combined relative distribution determined from symbols CPi and CPm with a second combined relative distribution determined from a symbol CPj and the symbol CPm, with 4 j W, and m G [ 0; N - 1].

3. Method according to any one of the preceding claims in which a particular probability distribution mask,yj is determined according to a reliability level determined for the symbols CPi and CPj and / or a reliability level determined for the difference between these symbols.

4. Method according to any one of the preceding claims in which a relative distribution P^j is convolved with a Kronecker distribution with a peak at 0 when the number of symbols which separate symbols CPi and CPj in the frame is less than a threshold, and with a uniform distribution when this number is greater than or equal to said threshold, the threshold being determined according to a characteristic of the communication channel.

5. A method according to any one of claims 1 to 3 wherein a relative distribution P is convolved with a probability distribution mask^ intermediate between a Kronecker distribution [0] and a uniform distribution U such that mask^y = « / / / [0] + ( 1 - U> the parameter aiU being determined according to a characteristic of the communication channel.

6. A method according to any preceding claim wherein a maskzyy- probability distribution is determined according to the number of symbols separating the symbols CPi and Cpj in the frame and a level of temporal variability of the channel.

7. A method according to any preceding claim wherein the method is such that a CPi symbol is a sequence of complex values obtained by applying a particular cyclic shift to a root sequence of size K, a CPi sequence being received on K subcarriers of an OFDM symbol.

8. Device for demodulating a data frame comprising N information words Fn n 1 in which a word P, occupying a position FO " ' A'-ll ie [0, N - 1] in the frame is modulated by a symbol Cpj from a dictionary of K symbols, the device comprising a processor (702) coupled to a memory (701) in which are recorded program instructions (703) configured to implement the following steps: - Determination, for a plurality of symbols CPi and Cpj of the frame, with / e [ 0, N - 1], of a vector of K probabilities Pj[j, called relative distribution, comprising probabilities associated with K possible values of an estimated difference between the symbols CPj and Cpp - Combination of a relative distribution P^j with a particular probability distribution Hiask^- determined according to a characteristic of the communication channel, - Demodulation of the frame from at least a part of the combined distributions.

9. A communication terminal comprising a demodulation device according to claim 8.

10. A computer program comprising instructions configured to implementing a demodulation method according to any one of claims 1 to 7, when the instructions are executed by a processor.

11. Computer-readable information medium on which are recorded instructions configured to implement a demodulation method according to any one of claims 1 to 7.

Images