Method, device and program for demodulating a data frame

Abstract

The invention relates to a method for demodulating a signal transmitted over a transmission channel, on which a frame of N binary words modulated by a particular symbol C pi from a dictionary of symbols is received (200), wherein the method comprises the steps of determining (201) a set E of relative distributions P i / j that are representative of a difference between the symbols C pi and C pj in the frame; determining (202), for each relative distribution P i / j in the set E, a partial relative distribution (F) by connecting a first relative distribution determined on the basis of the symbols C Pi and C pm with a second relative distribution determined on the basis of a symbol C Pj and the symbol C Pm ; consolidating (203) one of the relative distributions P i / j by recombining the determined partial relative distributions (F); and demodulating (205) the frame on the basis of at least one portion of the set E of consolidated relative distributions.

Description

[0001] DESCRIPTION Title: Method, device and program for demodulating a data frame Technical field The invention generally belongs to the field of telecommunications and more particularly relates to a method for improving 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 Communication systems are known which rely on a relative representation of the information for the purpose of its transmission and / or its processing. A common example is the use of differential modulations. Consider for example a frame of 5 symbols [^^0, ^^1, ^^2, ^^3, ^^4], each encoding ^^ bits of information, and thus being able to take 2 ^^ values. A possible differential representation of the frame can be [^^0⁄ 1 , ^^2, ^^2 − ^^3, ^^4 − ^^3]. 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 ^^). Such a representation can be used for transmission or signal processing purposes within the communication chain. For example, when variations between consecutive samples are small, transmitting differences between samples can be particularly effective. Such a differential representation of the frame can also be useful in certain receivers, for example when receiving a signal modulated by the cyclic rotation of a root sequence of complex symbols, such as CCSK modulation (for Cyclic Code-Shift Keying in English). 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, 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. For example, by choosing a root sequence composed of the 4 complex symbols [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' could correspond to the transmission of the sequence [a; b; c; d]; the binary word '01' could correspond to the transmission of the sequence [d; a; b; c]; the binary word '10' could correspond to the transmission of the sequence [c; d; a; b], etc. Knowledge of the root sequence allows the receiver to demodulate each symbol of the frame by cross-correlation with the root sequence. Demodulation can, for example, be carried out by cross-correlation of the sequences received with a particular sequence of the frame, for example a pilot sequence, whose shift with the root sequence is known to the receiver.Thus, it is the difference between the respective offsets of the sequences of the frame that allows the demodulation. It is thus necessary to have a good knowledge of the differences between the sequences of the same frame to carry out such demodulation. 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. There is therefore a need for a method that makes it possible to improve the demodulation performance, in particular when a communication is based on a relative representation of the information. Summary of the invention To this end, a method is proposed for demodulating a signal transmitted on a transmission channel on which a frame comprising ^^ information words, a word ^^ is received. ^^with ^^ ∈ [0; ^^ − 1] being modulated by a particular symbol ^^^^^^ from a dictionary of ^^symbols, the method comprising the following steps: - Determination of a set ^^ of probability distributions, called relative distributions, a relative distribution ^^ ^^ / ^^ being representative of the respective probabilities of a plurality of possible values ​​of the difference between symbols ^^ ^^^^ and ^^ ^^^^ from a plurality of couples (^^ ^^^^ ; ^^ ^^^^ ) formed from the symbols composing the frame, with ^^, ^^ ∈ [0; ^^ − 1]- For each relative distribution of the set ^^: - Determination of at least one partial relative distribution ^^ (^^) ^ ^ / ^^ by relating a first relative distribution determined from symbols ^^ ^^^^ and ^^ ^^^^with a second relative distribution determined from a symbol ^^^^^^ and the symbol ^^^^^^ , with ^^, ^^ ≠ ^^, and ^^ ∈ [0; ^^ − 1],- Determination of a relative distribution ^^ ^^ / ^^ consolidated, by recombination of partial relative distributions determined, - Demodulation of the frame from at least part of the consolidated relative distributions. Generally, the difference between symbols, or between values ​​associated with the symbols, corresponds in this document to a difference between digital representations associated with these symbols. The differences calculated between symbols may correspond to differences between indexes associated with the symbols or differences between the shifts of the sequences composing the symbols in the case of CCSK-type modulation, or even to a difference in angle or phase in the case of QPSK modulation (Quadrature Phase Shift Keying). Such differences are calculated according to modular arithmetic, in a finite group equipped with an additive law and a neutral element, for example in the group ^^ℤ / ^^^^ℤ.It is thus proposed to determine a differential representation of the frame in which we associate with each pair of symbols that can be formed with the symbols of the frame, a vector similar to a discrete probability distribution, whose size is equal to K, the cardinality of the dictionary of symbols and each element of which is a probability that the difference between two symbols is equal to a particular value. In this document, a relative distribution ^^. ^^⁄ ^^ corresponds to such a vector of K probabilities determined for a pair of symbols (^^ ^^^^ ; ^^ ^^^^ ). The determination of the relative distributions for each pair of symbols (^^ ^^^^ ; ^^ ^^^^ ) of a frame of ^^ symbols, with ^^ ∈ [0; ^^ − 1] and ^^ ∈ [0; ^^ − 1], results in a representation of the frame in the form of a matrix of probability distributions of the differences between symbols in the frame: Such a representation can be calculated for any frame of symbols without modifying the invention, independently of the type of modulation (CCSK, QPSK for Quadrature Phase Shift Keying, or Quadrature Phase Modulation in French, QAM for Quadrature Amplitude Modulation, or quadrature amplitude modulation in French, etc.), and more broadly for any sequence of discrete random variables. Consider for example the sequence of discrete random variables ^^ =[^^1 ^^2 … distribution law … ^^^^^^−1]. It is possible to express the matrix containing the set of differential random variablesY ∈ Ϝ ^^×^^^^ such that Y^^,^^ = ^^^^ − ^^^^ ∈ F^^ and the matrix of corresponding distributions ^^Y such that ^^Y^^,^^ = ⊛ ^^^^^^ where ⊛ is the cross-correlation operator. Given the similarity of the notions of sum and difference in the context of modular arithmetic in a finite field, we can also define the matrix containing the set of random variablesY ∈ Ϝ ^^×^^^^ such that Y^^,^^ = ^^^^ + ^^^^ ∈ F^^ and the matrix of corresponding distributions ^^Y such that que is this time the convolution operator. In this document we note "Relative distribution ^^ ^^⁄ ^^ » the distribution of the random variable resulting from the difference (or sum) of the two random variables ^^ ^^ and ^^ ^^ . In other words, for each symbol C Piat a position i in the frame, and for each symbol Ck of the dictionary (C1, C2, ... , CK), we determine a probability vector P(CPi = Ck), in which P(CPi = Ck) is the probability that the symbol at position i is the symbol Ck. Such a distribution is for example determined in a classical way by cross-correlation operations of the symbol at position i with the different symbols of the dictionary. Each symbol ^^ ^^^^ of the frame is thus represented by a random variable X i , so that the difference between two symbols ^^ ^^^^ and ^^ ^^^^ of the frame is, in the sense of the present invention, a differential random variable Y^^,^^ = ^^^^ − ^^^^ ∈ F^^ whose distribution, called relative distribution, is noted ^^ ^^⁄ ^^. It should also be noted that by construction, the diagonal of the matrix is ​​expected to contain distributions whose maximum is reached for index 0 because the difference between the index of a particular symbol relative to itself is zero. Furthermore, a form of symmetry is present in the matrix in the sense that the offset of the symbol ^^ relative to the symbol ^^ corresponds to the inverse offset of the symbol ^^ relative to the symbol ^^. This relative representation of the frame is determined a posteriori, from the received signal. Such a relative a posteriori representation is to be distinguished from a classical differential modulation in which the information is modulated differentially by the transmitter, that is to say in which an information word is modulated by a transition between two consecutively transmitted symbols.Thus, the implementation by a receiver of the method which is the subject of the present invention does not require any particular shaping of the signal by the transmitter, the symbols being able to be transmitted independently of each other. It is then proposed to determine relative distributions called partial ^^ (^^) ^. ^ / ^^ , determined on the one hand from the relative distributions determined for the symbols ^^ ^^^^ and ^^ ^^^^ and on the other hand from the relative distributions determined for the symbols ^^ ^^^^ and ^^ ^^^^. In other words, we determine an index difference between a first symbol and a second symbol by transitivity, that is to say from a difference between the first symbol and a third symbol and from a difference between the second symbol and the same third symbol. We thus obtain a plurality of estimates of the difference between the first and the second symbol based on different symbols. The different partial relative distributions ^^ (^^) ^ ^ / ^^ are then combined by product to obtain a consolidated version of a relative distribution ^^ ^^⁄ ^^ . The frame can then be demodulated from the consolidated information. For example, when the first symbol of the frame is known to the receiver by convention, then the consolidated difference between the different symbols of the frame and the first symbol, the ^^ ^^⁄ 0for ^^ ∈ [1 ; ^^ − 1], allows improved demodulation of the other symbols. The general concept of the invention is thus based on a combination of the probabilities of differences between digital representations associated with the symbols of the frame by relying on the relationships between variables inherent in such a representation of the information, with the aim of improving the quality of the estimation of this relative information. The method significantly improves the performance of the demodulation of a frame, in particular in communication systems which rely on a relative representation of the information for its transmission and / or its processing. According to a particular embodiment, the method is such that a symbol ^^ ^^^^ is a sequence of complex values ​​obtained by applying a particular cyclic shift to a root sequence of size ^^, a sequence ^^ ^^^^being transmitted on ^^ 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. The 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 Figure 1. The root sequence (and therefore all its cyclic shifts) being known to the receiver, the transmitted CCSK sequences can then serve as pilot sequences for synchronization and channel estimation, while carrying information.According to a particular realization, a relative distribution ^^. ^^ / ^^ is a vector of size ^^ in which each element ^^ ^^ / ^^ [^^] is a probability that a difference between the symbols ^^ ^^^^ and ^^ ^^^^ of the frame corresponds to the value ^^. According to a particular embodiment, the method comprises at least one step of normalizing the probabilities. It may be necessary to normalize the distributions obtained in the different steps of the method so that their sums are equal to 1 in accordance with their probabilistic nature. According to a particular embodiment, the step of determining a partial relative distribution ^^ (^^) ^ ^ / ^^ includes a cross-correlation operation between a relative distribution and a relative distribution ^^ ^^ / ^^ , or between a relative distribution ^^ ^^ / ^^ and a relative distribution ^^^^ / ^^ with ^^, ^^ ^^ and ^^ ∈ [0; ^^ − 1]. In other words, for relative distributions ^^ ^^ / ^^ associated with relative variables of the form (^^ − ^^), it is proposed to define partial relative distributions according to one or more of the following operations, where ⊛ represents the cross-correlation and ̅ ^̅ ̅^^̅ ̅^⁄̅ ^^ the mirror distribution of ^^ ^^⁄ ^^ on the finished body: When the relative distributions between symbols are expressed by index differences in a finite field (i.e. modulo K for a dictionary of K symbols), the relating of the indexes of the symbols can be carried out by a cross-correlation operation. According to a particular embodiment, the step of determining a partial relative distribution ^^ (^^) ^ ^ / ^^ includes a convolution operation between a relative distribution and a relative distribution ^^^^ / ^^, with ^^, ^^ ^^ and ^^ ∈ [0; ^^ − 1]. Thus, it is also proposed to define partial relative distributions by one or more convolution operations among the following operations, where ∗ is the convolution operator and ̅ ^̅ ̅^^̅ ̅^⁄̅ ^^ the mirror distribution of ^^^^⁄ ^^ over the finite field: Thus, the relating of the relative distributions is done by a sum in a finite field (i.e. modulo K for a dictionary of K elements), i.e. by a convolution operation. In a particular implementation, the method is such that the recombination step does not take into account the partial relative distributions ^^ (^^) ^ ^ / ^^ determined from a relative distribution ^^ ^^ / ^^ and / or a relative distribution ^^ ^^ / ^^. Such an arrangement makes it possible to guard against certain "self-influence loops" by masking the data so as to avoid updating a relative distribution from data from this same relative distribution (or from the mirror distribution). This kind of phenomenon can occur in an iterative algorithm when the update of the value of a variable involves the intrinsic information of this variable (i.e. information from the observation of the variable that we wish to update) rather than extrinsic information (i.e. information from the observation of the other variables linked to it). It is thus proposed not to take into account relative distributions ^^ ^^ / ^^(nor the mirror distribution̅ ^̅ ̅^̅ ̅ ) to determine a relative distribution (^^) ^^⁄ ^^ rtial ^^^^ / ^^in order not to influence the result of the recombination. In other words, we avoid taking into account a distribution ^^^^ / ^^ (which could be calculated by mirror of ^^^^ / ^^ - operation which we note ̅ ^̅ ̅^̅^^⁄ ̅ ^^) nor ^^^^ / ^^ (which could be calculated by mirror of ^^^^ / ^^ - operation noted ̅ ^̅ ̅^^̅^⁄ ̅ ^^). Indeed, there exists a form of symmetry in the matrix of relative distributions so that ^^ ^^ / ^^ is similar to (but not necessarily equal to) the mirror of According to a particular embodiment, the steps of determining a partial relative distribution and of recombination are repeated, the method further comprising at each iteration, a step of recombination with the relative distributions of the set ^^ initially determined. In this way, the consolidated relative distributions are used in a subsequent iteration to further consolidate the relative distributions. This recombination then comprises a term-by-term product of the relative distributions of the set E and the corresponding relative distributions consolidated at the previous iteration, or the relative distributions updated during the current step.According to another aspect, there is provided a device for demodulating a signal transmitted on a transmission channel on which a frame comprising ^^ information words is received, a word ^^^^ with ^^ ∈ [0; ^^ − 1] being modulated by a particular symbol ^^^^^^ from a dictionary of K symbols, the device comprising a processor coupled to a memory in which instructions are recorded suitable for implementing the following steps, when they are executed by the processor: - Determination of a set ^^ of probability distributions, called relative distributions, a relative distribution ^^. ^^ / ^^ being representative of the possible values ​​of the difference between symbols ^^ ^^^^ and ^^ ^^^^ from a plurality of couples (^^ ^^^^ ; ^^ ^^^^ ) formed from the symbols composing the frame, with ^^, ^^ ∈ [0; ^^ − 1], as well as their respective probabilities, - For each relative distribution ^^ ^^ / ^^of the set ^^: - Determination of at least one partial relative distribution ^^ (^^) ^ ^ / ^^ by relating a first relative distribution determined from symbols ^^ ^^^^ and ^^ ^^^^ with a second relative distribution determined from a symbol ^^^^^^ and the symbol - Determination of a relative distribution consolidated, by recombination of partial relative distributions determined, - Demodulation of the frame from at least a part of the set ^^ of consolidated relative distributions. The invention also relates to a radiofrequency receiver comprising a demodulation device as described above, as well as a communication terminal or a base station comprising such a receiver. In a particular embodiment, the different steps of the demodulation method are determined by computer program instructions. 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.This program may use any programming language, and may be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other desirable form. The invention also provides 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. 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.On the other hand, the information carrier 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 a network such as the Internet. 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. The various embodiments or features mentioned above may be added independently or in combination with each other, at the steps of the demodulation method. The devices, terminals, programs and information carriers have advantages similar to those conferred by the method to which they correspond.Brief description of the figures Other characteristics and advantages will appear on reading a preferred embodiment described with reference to the appended drawings among which: - Figure 1 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, - Figure 2 is a flowchart representing the main steps of a demodulation method according to a particular embodiment, - Figure 3 is a table showing the variables involved in the calculation of partial distributions in the case of a set of three random variables, - Figure 4 is a table showing variables likely to be involved in the consolidation of a partial distribution, - Figure 5 illustrates an example of a calculation tree governing the execution of two iterations of the demodulation method with a view to consolidating a relative distribution ^^. 1⁄ 0, in a particular embodiment, - Figure 6 illustrates a particular embodiment of a calculation tree capable of governing the execution of two iterations of the demodulation method with a view to consolidating a relative distribution ^^ 1⁄ 0, in which branches likely to be masked have been highlighted, - Figure 7 is a diagram representing the architecture of a device suitable for implementing the demodulation method in a particular embodiment. detailed In the description which follows, 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 can be replaced by other modulation techniques, such as QPSK, or QAM (Quadrature Amplitude Modulation), without it being necessary to modify the invention. Figure 2 illustrates the main steps of a demodulation method according to a particular embodiment. The method is for example implemented by a radiofrequency receiving device, such as a connected object, a terminal, user equipment, a base station, etc. During a first step 200, the method comprises the reception of a data frame transmitted by another device. In a particular embodiment, the frame is a CP-OFDM frame comprising a plurality of CCSK sequences, each of the ^^ time steps comprising a CCSK sequence of size ^^ distributed over all the subcarriers in frequency, as shown in Figure 1.The received frame thus comprises ^^ binary words of size ^^ bits, each binary word ^^. ^^ of the frame being modulated by a sequence of complex values^^^^^^ of size ^^ = 2 ^^, with ^^ ∈ [0; ^^ − 1].At step 201, for each sequence ^^ ^^^^of the frame, a difference with each of the other sequences is estimated. The difference operator in question here 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. In a particular embodiment, the estimated difference is representative of a difference between index values ​​associated with the symbols in a symbol dictionary, following an indexing system equal to the set {0, 1, …, K-1} up to an isomorphism, and their respective probabilities. More particularly, the index values ​​associated with the symbols belong to a finite group of size K, in which a difference between two values ​​of the set is always also a value belonging to said index set.Each symbol in the dictionary is thus associated with an index, typically a value from 0 to K-1 when the dictionary includes K symbols. We can represent a vector ^^. ^^ (respectively ^^ ^^ ) as the probability distribution of symbol A (respectively of symbol B). For example, if K=4, we can have ^^ ^^ = [0.1,0.1,0.1,0.7]. The indexing system determines that the corresponding symbol probably has the index symbol value 3. Thus, ^^ ^^ / ^^ = [0.1,0.7,0.1,0.1] is obtained by convolution or cross-correlation of the symbol distributions ^^ ^^ and ^^ ^^and means that the difference (modulo K=4) between the indices associated with A and B is probably equal to 1. As indicated, such a difference is estimated in a finite group of size K, i.e. modulo the cardinality of the symbol dictionary when assuming an indexing in the form {0, 1, …, K-1}. In a particular implementation, the index values ​​are defined by the group ^^ℤ / ^^^^ℤ, considering modular arithmetic on the remainders of division by ^^^^ and ^^ a strictly positive integer, ℤ being the set of relative integers. For example, with m=2 and K=4, we obtain a set of indices [0,2,4,6] such that any difference (or sum) modulo ^^^^ 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… We thus obtain a set of relative a priori distributions, that is to say a set noted ^^ of probability distributions which express differences between numerical values ​​representative of the symbols, and which are estimated directly from the received symbols. In a particular embodiment, this processing results in a representation of the OFDM frame in the form of a matrix of probability distributions (or relative distributions in the sense of the invention) of the differences between symbols, that is to say of the relative offsets between the CCSK sequences of the frame:. In this matrix, each index ^^ ^^⁄ ^^thus contains a vector of size ^^ (allowing the representation of all possible symbols, which can correspond, in the case of CCSK modulation, to the K possible shifts of a sequence of size K), an element ^^ ^^⁄ ^^ [^^] of the vector containing the probability that the relative shift between the symbols ^^ ^^^^ and ^^ ^^^^ of the OFDM frame corresponds to the value ^^. Consider for example a frame containing 5 CCSK symbols of size 4 (each encoding 2 bits of information). The cardinality of the symbol dictionary is therefore equal to 4. If ^^ 3⁄ 5=[0.2, 0.3, 0.1, 0.4], then the most likely relative shift of symbol 3 relative to symbol 5 is Argmax (^^3⁄ 5 ) = 3. In other words, the values ​​of these two symbols are related by the relation ^^3 = ^^5 + 3 ^^^^^^ 4. As already noted, it is expected by construction that the diagonal of such a matrix contains distributions whose maximum is reached for index 0 (the shift of a CCSK symbol relative to itself is 0). We can also note a form of symmetry in the matrix, the shift of the symbol ^^ with respect to the symbol ^^ corresponding to the inverse shift of the symbol ^^ with respect to the symbol ^^: ^^^^⁄ ^^ [^^] = ^^^^⁄ ^^ [^^ − ^^ ^^^^^^ ^^]. Thus, taking the previous example, ^^3⁄ 5 = [0.2, 0.3, 0.1, 0.4] andArgmax (^^3⁄ 5 ) = 3 , then it is expected that ^^5⁄ 3 ≈ [0.2, 0.4, 0.1, 0.3] andArgmax (^^5⁄ 3 ) = 1, up to noise. In other words, the values ​​of these two symbols are related by ^^5 = ^^3 − 3 ^^^^^^ 4 = ^^3 + 1 ^^^^^^ 4.Of course, it is possible to determine only a subset of these relative distributions without modifying the invention. During a step 202, for each relative distribution ^^. ^^ / ^^ from the matrix determined in step 201, at least one relative distribution called partial ^^ (^^) ^ is determined ^ / ^^ by relating a first relative distribution determined from symbols ^^ ^^^^ and ^^ ^^^^ with a second relative distribution determined from a symbol ^^ ^^^^ and the symbol ^^ ^^^^ , with In this step, partial versions of all relative distributions are calculated using the pairs of relative distributions calculated in step 201. In a particular embodiment, these partial versions are obtained using a cross-correlation operation between the relative distributions: This relationship between distributions is a direct consequence of the transitivity of the difference operation between the underlying random variables. In a particular embodiment, relative relationships based on sums rather than differences are considered, the cross-correlation operator is then replaced by the convolution operator without modifying the invention. Figure 3 is a table showing the variables involved in the calculation of the ^^3 = 27 partial distributions in the case of a set of three random variables, for example a CCSK-CP-OFDM frame of size ^^ = 3. This table indicates the relative distributions x and y from which a partial relative distribution ^^(^^) ^ ^⁄ ^^ is obtained. For example, the partial relative distribution is performed by cross-correlation between distributions ^^ 2⁄ 1 and ^^ 0⁄ 1. According to a particular embodiment, the partial relative distributions ^^ (^^) ^ ^ / ^^ determined from a relative distribution ^^ ^^ / ^^ and / or a relative distribution ^^ ^^ / ^^ are not calculated. The method comprises a step 203 during which a relative distribution ^^ is calculated from the distributions rel (^^) a ⁄ b partial atives ^^ ^^⁄ ^^ determined in step 202. For this, it is proposed to calculate a product of the partial relative distributions ^^(^^) ^ ^⁄ ^^ calculated: According to a particular embodiment, the method comprises a step 204 during which the distribution ^^ obtained by the product of the distribut (^^) ^ ^ / ^^ partial relative ions ^^ ^^⁄ ^^ is recombined with the corresponding prior distribution, that is to say with the relative distribution ^^ ^^ / ^^calculated in step 201. This recombination makes it possible to obtain the consolidated relative distributions, also called a posteriori relative distributions. These consolidated relative distributions make it possible to update a set ^^′ of relative distributions, each distribution of which is then consolidated. The table in Figure 4 shows variables likely to intervene in the consolidation of one of the ^^2 = 9 partial distributions. For example, the consolidation of the relative distribution ^^ can be based on the product (1) 1 it of the partial distributions 2 1 and ^^ ( ) 2 ⁄ 21. According to a particular embodiment, steps 202 to 204 are executed iteratively. At each iteration, the a priori relative distributions are combined, according to steps 202 to 204, with the consolidated relative distributions of the set ^^′ received from the previous iteration to obtain new estimates of the relative distributions, herein referred to as a posteriori. These new estimates are then used as a basis for calculating the new partial relative distributions of the current iteration, themselves used to determine the information to be provided at the following iteration by updating the set ^^′. In other words, the relative distributions of an iteration ^^ are obtained by relating relative distributions ^^′ determined during an iteration ^^ − 1 with a priori relative distributions of the set ^^ initially determined.In the first iteration, the matrix ^^′ is initialized from distributions determined for the set ^^. Figure 5 illustrates an example of a lattice (or computational graph) governing the execution of two iterations of the method with a view to consolidating a relative distribution ^^. 1⁄ 0, always for a set of 3 random variables, such as a CCSK-CP-OFDM frame of size 3 (an equivalent graph, not shown here, would be executed in parallel for the purpose of consolidating the other relative distributions). The bold arrows represent the a priori information, i.e. the information available about a variable at the initialization of the process. The a posteriori value of a relative distribution can therefore be defined as the product of the information from the previous iteration by the a priori information. If the result of this calculation is likely to be used again due to the execution of an additional iteration of the process, it is important to guard against certain “self-influence loops”. For this, according to a particular implementation, a masking step is implemented to avoid such influence loops.Masking may consist of not taking into account certain partial relative distributions at the recombination step 203, or simply not calculating these distributions at the step 202. In Figure 4, the combination distributions likely to create a self-influence loop have been highlighted by a speckled or striped background pattern. For example, partial relative distributions. are likely to create a self-influence loop when used to obtain a relative distribution ^^ 2⁄ 0because such a recombination involves the intrinsic information of this variable, that is to say, resulting from the observation of the variable that one wishes to update, or from the observation of the symmetric variable. The cells whose grid is speckled in Figure 4 are partial relative distributions constructed on the basis of the intrinsic information, that is to say, directly resulting from the observation of the variable that one wishes to modify. The cells whose grid is striped are partial distributions constructed on the basis of the symmetric relative distribution. Indeed, the matrix ^^ determined in step 201 being “symmetric”, the symmetric value can be considered as the intrinsic value with respect to subsequent updates, and it may be desirable not to take it into account either.Figure 6 shows the calculation graph of Figure 5 in which the distributions likely to produce a self-influence loop have been highlighted by dotted arrows. The masking operation may thus consist of not taking into account the calculation branches comprising dotted arrows in the recombination step 203. Only the extrinsic information is then retained, i.e. the information that can be drawn about a variable by simply observing the other variables linked to it, and the use of intrinsic information is avoided, i.e. the information that can be drawn about a variable by simply observing the latter. Thus, in a particular embodiment, it is proposed not to take into account the partial relative distributions constructed on the basis of the intrinsic information: for example, the consolidated value of ^^. 0⁄ 1should not depend on the partial relative distribution ^^ (1) 0 ⁄ 1 = ^^ 0⁄ 1 ⊛^^ 1⁄ 1 which contains the intrinsic value ^^ 0⁄ 1 . In a particular embodiment, it is proposed not to take into account the partial distributions constructed on the basis of the symmetrical relative distribution: for example, the consolidated value of ^^ 0⁄ 1 should not depend on the partial relative distribution ^^ ( 0 ) 0 ⁄ 1 = ^^ 0⁄ 0 ⊛ ^^ 1⁄ 0 which contains the symmetrical value ^^ 1⁄ 0 . Indeed, the matrix ^^ considered being "symmetrical" (^^^^⁄ ^^ [^^] = ^^^^⁄ ^^ [^^ − ^^ ^^^^^^ ^^]) – the symmetrical value can be considered as the intrinsic value, up to noise, with respect to subsequent updates. According to a particular embodiment, the method comprises at least one step of normalization of the probabilities ^^ ^^ / ^^[^^]. It may be necessary to normalize the distributions obtained in the different steps of the process so that their sums are equal to 1 in accordance with their probabilistic natures. Furthermore, although the process is described here with reference to discrete distributions, the present proposal can be generalized to continuous distributions, for example by approximating the continuous distribution by a discretized distribution, or by modeling the distributions by their parameters (for example the mean ^^ and the variance ^^ as parameters of a normal distribution). It is then appropriate to express the relationship between the parameters of the relative distributions and the partial relative distributions (for the calculation of the partial relative distributions), as well as the impact of the product reduction of the partial distributions on the parameters of the relative distribution thus obtained (for the calculation of the product reduction).The method finally comprises a demodulation step 205 during which at least part of the relative a posteriori distributions of the set E' are used. For example, the demodulation can be based on the offsets between CCSK sequences relative to a sequence of the frame taken as reference (in other words, using a particular row of the matrix updated after one or more iterations of the method). Knowledge of the relative offsets between sequences of the same frame allows offset demodulation, even when the offset of a CCSK sequence relative to the root sequence is unknown.When the relative offsets between each of the sequences transmitted in the frame can be determined, for example when all the symbols in the frame are subject to the same channel, it is possible to perform offset demodulation using the integrity check data of the frame to determine the offset to be applied to recover the transmitted binary words. To do this, the received CCSK sequences can be demodulated by considering a zero offset of a sequence in the frame taken as a reference. With the relative offsets known, the binary words of the frame are obtained. An integrity check, for example a CRC, is then used to determine whether the decoded frame is correct. If this is not the case, i.e. if the integrity check fails, a new demodulation attempt is made after applying an offset to the CCSK sequences in the frame. This is done until the integrity check shows correct demodulation.Figure 7 represents a simplified architecture of a device 700 adapted to implement the demodulation method according to a particular embodiment. 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 a particular embodiment of the demodulation method described in relation to Figure 2, and in particular the steps of determining a set ^^ of probability distributions, called relative distributions, a relative distribution. being representative of the possible values ​​of the difference between the index values ​​associated with symbols ^^ ^^^^ and ^^ ^^^^ from a plurality of couples (^^ ^^^^;^^^^^^) formed from the symbols composing the frame, with ^^, ^^ ∈ [0; ^^ − 1] as well as their respective probabilities, said difference being calculated in a finite group of size ^^; for each relative distribution ^^ ^^ / ^^ of the set ^^, of determination of at least one partial relative distribution ^^ (^^) ^ ^ / ^^ by relating a first relative distribution determined from symbols ^^ ^^^^ and ^^ ^^^^ with a second relative distribution determined from a symbol ^^^^^^ and the symbol ^^^^^^ , with ^^, ^^ ≠ ^^, and ^^ ∈ [0; ^^ − 1], and determination of a relative distribution ^^ ^^ / ^^ consolidated, by recombination of partial relative distributions ^^ (^^) ^ ^ / ^^determined, and demodulation of the frame from at least part of the consolidated relative distributions. 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. 2. 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 signals on a plurality of orthogonal carriers.In a particular embodiment, the communication means 704 are 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 CCSK sequence of size K distributed over all the frequency subcarriers. The device 700 also comprises an OFDM demodulator 705 adapted to generate N vectors of K values ​​from the frame received by the communication means 704 on K subcarriers, the K values ​​corresponding to the K complex values ​​composing a CCSK sequence of K elements coding for an information word of the frame. The device 700 also comprises a module 706 for determining a matrix comprising a set ^^ of probability distributions, called relative distributions, each element ^^. ^^ / ^^of the matrix being a vector of K probabilities representing the possible values ​​of the difference between the index values ​​associated with the ^^ ^^^^ and ^^ ^^^^ of a plurality of pairs of sequences (^^ ^^^^ ; ^^ ^^^^) formed from the sequences composing a frame received by the communication means 704, with ^^ ∈ [0; ^^ − 1] and ^^ ∈ [0; ^^ − 1], as well as the respective probabilities of these differences, a difference being calculated in a finite group of size K, or modulo the cardinality of the symbol dictionary considering the index set {0,1,…,K-1}. The module 706 is for example implemented by computer program instructions configured to calculate a difference between two sequences of the frame by a cross-correlation and / or convolution operation, determine a probability that this difference corresponds to a particular shift, and store the result of the difference between the elements of a pair (^^^^^^^ ; ^^^^^^) of sequences at the coordinates (^^; ^^) in the matrix. The device further comprises a module 707 for calculating partial relative distributions.The module is implemented by computer program instructions configured to relate a first relative distribution determined from ^^ symbols. ^^^^ and ^^ ^^^^ with a second relative distribution determined from a symbol ^^ ^^^^ and the symbol ^^^^^^ , with i,j≠ ^^, and ^^ ∈ [0; ^^ − 1]. The relationship is carried out by a cross-correlation and / or convolution operation. The module 707 carries out the relationship from the data of the matrix determined by the module 706. In other words, the module 707 extracts the different pairs of relative distributions from the matrix to calculate partial relative distributions by a cross-correlation and / or convolution operation. The device comprises a recombination module 708 adapted to consolidate relative distributions ^^ of the matrix by (^^) ^ ^ / ^^ partial relative distributions shot ^^ ^^ / ^^determined by module 707. For this, module 708 includes program instructions configured to produce a product of partial relative distributions ^^ (^^) ^ ^ / ^^ ,^^ ∈ [0;^^ − 1], for each distribution ^^^^ / ^^. In a particular embodiment, the module 708 is further configured to apply a filtering of the partial relative distributions before the product reduction, in particular with a view to a new iteration of the method. Such a filtering step is for example implemented by program instructions configured not to take into account the partial relative distributions constructed on the basis of the intrinsic information, that is to say on the basis of the relative distribution for which the partial relative distribution is calculated, nor of its mirror relative distributions. For example, the module is configured so that the distribution ^^ 0⁄ 1 is not consolidated from a partial distribution of = ^^ 0⁄ 1 ⊛^^ 1⁄ 1 , because such a partial distribution depends on ^^ 0⁄ 1 , and therefore of intrinsic value ^^ 0⁄ 1The device 700 comprises a module 709 adapted to multiply term-by-term the distributions determined by the module 708 with the relative distributions a priori, determined by the module 706. The device 700 finally comprises a demodulation module 710 adapted to carry out a demodulation of the symbols transmitted in the frame from at least a part of the relative distributions consolidated by the module 709.For example, the module 710 is implemented by program instructions adapted to obtain the offset of a predetermined sequence of the frame, for example of a pilot sequence whose position and offset are known by convention, and to demodulate the other sequences of the frame using the consolidated relative distributions, and in particular based on the consolidated relative offsets between the known sequence and the other sequences of the frame, for example from the consolidated offsets in one or more particular lines of the matrix updated by the modules 707 to 709. In a particular embodiment, the device is integrated into a communication terminal, a connected object, a vehicle, a gateway, an access point or even a base station.

Claims

CLAIMS 1. Method for demodulating a signal transmitted on a transmission channel on which a frame comprising ^^ information words is received, a word ^^^^ with ^^ ∈ [0; ^^ − 1] being modulated by a particular symbol ^^ ^^^^ of a dictionary of ^^ symbols, the method comprising the following steps: - Determination (201) of a set ^^ of probability distributions, called relative distributions, a relative distribution ^^ ^^ / ^^ being representative of the possible values of the difference between symbols ^^ ^^^^ and ^^ ^^^^ from a plurality of pairs (^^^^^^; ^^^^^^) formed from the symbols composing the frame, with ^^, ^^ ∈ [0; ^^ − 1] as well as their respective probabilities, - For each relative distribution ^^ ^^ / ^^ of the set ^^: - Determination (202) of at least one partial relative distribution ^^ (^^) ^ ^ / ^^by relating a first relative distribution determined from symbols ^^ ^^^^ and ^^ ^^^^ with a second relative distribution determined from a symbol ^^^^^^ and the symbol ^^^^^^ , with ^^, ^^ ≠ ^^, and ^^ ∈ [0;^^ − 1],- Determination (204) of a relative distribution ^^ ^^ / ^^ consolidated, by recombination of partial relative distributions ^^ (^^) ^ ^ / ^^ determined, - Demodulation (205) of the frame from at least part of the consolidated relative distributions.

2. Method according to claim 1 in which a symbol ^^ ^^^^ is a sequence of complex values obtained by applying a particular cyclic shift to a root sequence of size ^^, a sequence ^^ ^^^^ being transmitted on ^^ subcarriers of an OFDM symbol.

3. A method according to any preceding claim wherein a relative distribution ^^ ^^ / ^^is a vector of size ^^ in which each element ^^ ^^ / ^^ [^^] is a probability that a difference between the symbols ^^ ^^^^ and ^^ ^^^^ of the frame corresponds to the value ^^.

4. Method according to any one of the preceding claims such that it comprises at least one step of normalizing the probabilities.

5. Method according to any one of the preceding claims in which the step of determining a partial relative distribution ^^ (^^) ^ ^ / ^^ includes at least one cross-correlation operation between a relative distribution and a relative distribution ^^ ^^ / ^^ , or between a relative distribution ^^^^ / ^^ and a relative distribution ^^^^ / ^^ with ^^, ^^ ^^ et ^^ ∈ [0;^^ − 1].

6. A method according to any preceding claim wherein the step of determining a partial relative distribution ^^ (^^) ^ ^ / ^^includes at least one convolution operation between a relative distribution ^^ ^^ / ^^ and a relative distribution ^^ ^^ / ^^ , with 7. Method according to any one of the preceding claims in which the recombination step does not take into account the partial relative distributions ^^ (^^) ^ ^ / ^^ determined from a relative distribution ^^ ^^ / ^^ and / or determined from a relative distribution ^^ ^^ / ^^.

8. Method according to any one of the preceding claims in which the steps of determining a partial relative distribution and of recombination are repeated, the method further comprising at each iteration, a step of recombination with the relative distributions of the set ^^ initially determined.

9. Device for demodulating a signal transmitted on a transmission channel on which a frame comprising ^^ information words is received, a word ^^^^ with ^^ ∈ [0; ^^ − 1] being modulated by a particular symbol ^^ ^^^^ of a dictionary of ^^ symbols, the device comprising a processor coupled to a memory in which are stored instructions adapted to implement the following steps, when executed by the processor: - Determination of a set ^^ of probability distributions, called relative distributions, a relative distribution ^^ ^^ / ^^being representative of the possible values of the difference between symbols ^^ ^^^^ and ^^ ^^^^ from a plurality of couples (^^ ^^^^ ; ^^ ^^^^ ) formed from the symbols composing the frame, with ^^, ^^ ∈ [0; ^^ − 1], as well as their respective probabilities, - For each relative distribution of the set ^^: - Determination of at least one partial relative distribution by relating a first relative distribution determined from symbols ^^ ^^^^ and ^^ ^^^^ with a second relative distribution determined from a symbol ^^^^^^ and the symbol - Determination of a relative distribution ^^ ^^ / ^^ consolidated, by recombination of partial relative distributions ^^ (^^) ^ ^ / ^^determined, - Demodulation of the frame from at least a part of the set ^^ of consolidated relative distributions.

10. Communication terminal comprising a demodulation device according to claim 9.

11. Computer program comprising instructions adapted to the implementation of the steps of a demodulation method according to any one of claims 1 to 8, when the program is executed by a processor.

12. Information medium readable by a computer on which is recorded a computer program comprising instructions for the execution of the steps of a demodulation method according to any one of claims 1 to 8.

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