WO2018072480A1

WO2018072480A1 - Decoding method and device for overlapped multiplexing system

Info

Publication number: WO2018072480A1
Application number: PCT/CN2017/091968
Authority: WO
Inventors: 刘若鹏; 季春霖; 郑昊
Original assignee: 深圳超级数据链技术有限公司
Priority date: 2016-10-19
Filing date: 2017-07-06
Publication date: 2018-04-26
Also published as: CN107968697B; CN107968697A

Abstract

Disclosed are a decoding method and device for an overlapped multiplexing system. The method comprises: obtaining a received symbol sequence and a state transition relationship, wherein the received symbol sequence comprises a plurality of received symbols which is obtained after encoding a plurality of original input symbols by an overlapped multiplexing system and transmitting the encoded symbols via a channel, and the state transition relationship comprises a state transition relationship of different original input symbols at different moments corresponding to encoded output symbols; and calculating a posterior log-likelihood ratio of each original input symbol according to the received symbol sequence and the state transition relationship. The present invention resolves the technical problem in the prior art of being unable to output soft information of each bit using hard decoding decision method.

Description

Decoding method and device for overlapping multiplexing system

Technical field

The present invention relates to the field of overlapping multiplexing systems, and in particular to a decoding method and apparatus for an overlapping multiplexing system.

Background technique

Wireless communication systems are very different from wired communication systems. Because the system environment of wireless communication is very complicated, how to ensure the reliability of wireless communication systems to transmit information has become an important indicator for evaluating modern wireless communication systems. As the information receiving end, it is necessary to restore the original transmission information as much as possible, that is, when the transmission power and the signal-to-noise ratio are fixed, the bit error rate is as low as possible, and the reliability of the transmission information is ensured.

For the overlapping multiplexing system OvXDM with overlapping multiplexing times K, X represents any domain, which can be time T, frequency F, code division C, space S or hybrid H, etc., respectively, indicating overlapping time division multiplexing system OvTDM, overlapping frequency complex Use system OvFDM, overlapping code division multiplexing system OvCDM and so on.

In the OvXDM system, when performing sequence detection, the hard decision decoding algorithm is mostly used, and the maximum likelihood sequence generated by decoding the information is directly output, that is, the value in the sequence is only 0 or 1, and cannot be output. The soft information of each decoded bit cannot be used as a SISO (soft-in soft-out) decoding algorithm.

In view of the problem of using the hard decoding decision method in the prior art, the soft information of each bit cannot be output, and an effective solution has not been proposed yet.

Summary of the invention

The embodiments of the present invention provide a decoding method and apparatus for an overlap multiplexing system, so as to at least solve the technical problem that the hard decoding decision method in the prior art cannot output soft information of each bit.

According to an aspect of the embodiments of the present invention, a decoding method of an overlap multiplexing system is provided, including: acquiring a received symbol sequence and a state transition relationship, wherein the received symbol sequence includes: a plurality of received symbols, and the plurality of received symbols are The plurality of original input symbols are encoded by the overlapping multiplexing system and obtained after channel transmission, and the state transition relationship includes: a state transition relationship corresponding to the coded output symbols at different time points of different original input symbols; according to the received symbol sequence and state transition The relationship is calculated by the posterior log likelihood ratio of each original input symbol.

According to another aspect of the present invention, there is also provided a decoding apparatus of an overlap multiplexing system, comprising: an obtaining module, configured to acquire a received symbol sequence and a state transition relationship, wherein the received symbol sequence comprises: multiple receiving a symbol, a plurality of received symbols are encoded by an overlapping multiplexing system, and are transmitted through a channel The state transition relationship obtained after the input includes: a state transition relationship corresponding to the coded output symbols at different time points of different original input symbols; a calculation module, configured to calculate each original input symbol according to the received symbol sequence and the state transition relationship A posteriori log likelihood ratio.

In the embodiment of the present invention, the received symbol sequence and the state transition relationship may be acquired, and the posterior log likelihood ratio of each original input symbol is calculated according to the received symbol sequence and the state transition relationship, so that the decoding is completed after the decoding is completed. The bit error probability is the smallest, and the soft information of the relevant bit is output, that is, the log likelihood ratio, which solves the technical problem that the hard decoding decision method is used in the prior art, and the soft information of each bit cannot be output. Therefore, by using the solution provided by the foregoing embodiment of the present invention, the obtained log likelihood ratio can be used as the SISO (soft-in soft-out) decoding algorithm of the OvXDM system, thereby improving the success rate of decoding and reducing the decoded Bit error rate. Since this patent can directly output the optimal posterior probability (MAP, Log-MAP) or sub-optimal (Max-Log-MAP) posterior probability, it can be used with the subsequent soft decoding FEC module. The communication reliability of the system can be improved compared to the hard-decoded FEC module. At the same time, this patent can be used with the OvXDM module of Turbo structure, and the external information transmission and iteration between different OvXDM decoders. The low correlation external information transmission can improve the error performance of the system and strengthen the reliability of the communication system. Sex, get further system gain.

DRAWINGS

The drawings described herein are intended to provide a further understanding of the invention, and are intended to be a part of the invention. In the drawing:

1 is a flow chart of a decoding method of an overlay multiplexing system according to an embodiment of the present invention;

2 is a flow chart of a soft-in soft-out decoding method according to an embodiment of the present invention;

3 is a schematic diagram of convolutional coding of an alternative overlapping time division multiplexing system in accordance with an embodiment of the present invention;

4 is a tree diagram of an input-output relationship of an alternative overlapping time division multiplexing system in accordance with an embodiment of the present invention;

5 is a state transition diagram of an alternative overlapping time division multiplexing system in accordance with an embodiment of the present invention;

6 is a Trellis block diagram of an alternative overlapping time division multiplexing system in accordance with an embodiment of the present invention;

7 is a schematic structural diagram of an optional soft-in soft-out decoding according to an embodiment of the present invention;

FIG. 8 is a schematic diagram of a decoding apparatus of an overlap multiplexing system according to an embodiment of the present invention.

detailed description

In order to enable those skilled in the art to better understand the solution of the present invention, the following will be incorporated in the embodiments of the present invention. The embodiments of the present invention are clearly and completely described in the drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of the present invention.

It is to be understood that the terms "first", "second" and the like in the specification and claims of the present invention are used to distinguish similar objects, and are not necessarily used to describe a particular order or order. It is to be understood that the data so used may be interchanged where appropriate, so that the embodiments of the invention described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "comprises" and "comprises" and "the" and "the" are intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to Those steps or units may include other steps or units not explicitly listed or inherent to such processes, methods, products or devices.

Example 1

In accordance with an embodiment of the present invention, an embodiment of a method of decoding a method of an overlay multiplexing system is provided. It is noted that the steps illustrated in the flowchart of the accompanying drawings may be in a computer system such as a set of computer executable instructions. The execution is performed, and although the logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in a different order than the ones described herein.

FIG. 1 is a flowchart of a decoding method of an overlap multiplexing system according to an embodiment of the present invention. As shown in FIG. 1, the method includes the following steps:

Step S102: Acquire a received symbol sequence and a state transition relationship, where the received symbol sequence includes: a plurality of received symbols, where the plurality of received symbols are encoded by the overlapping multiplexing system and obtained after channel transmission, and the status is obtained. The transfer relationship includes: a state transition relationship corresponding to the coded output symbols at different time points of different original input symbols; and a corresponding soft-in soft-out flow chart is shown in FIG. 2 .

Specifically, according to the flow shown in FIG. 2, the flow of obtaining the posterior log likelihood ratio is as follows:

On the one hand, the receiving sequence is acquired, on the other hand, the prior probability is initialized at the same time; these two steps are to obtain the necessary parameters to calculate the current state transition parameter γ; and then further calculate the forward recursive parameter α and the backward recursion separately. The parameter β is calculated based on the calculated α, β, γ, and the posterior log likelihood ratio Lapp is calculated.

The calculation of each of the above parameters will be detailed in the subsequent embodiments.

Optionally, in the embodiment of the present invention, the OvTDM system is taken as an example for description, and other OvXDM systems can be similarly used. As shown in Figure 3, the OvTDM system is a waveform convolutional coding system, so there is no way to use traditional symbol-by-symbol detection when decoding. Figure 4 shows the input and output relationship tree diagram of the OvTDM system with binary (+1,-1) data at K=3, which is imaged in the OvTDM system. The data transfer status, as well as the node transfer relationship diagram of the OvTDM system, can be clearly seen, as shown in Figure 5. Therefore, the input-output relationship of the OvTDM system can be represented by a Trellis diagram (grid diagram), as shown in Figure 6.

Specifically, in the overlapping multiplexing system, the transmitting end performs waveform coding on the original input symbol sequence to obtain a sequence of encoding the output symbol sequence, and can determine a state transition of the different original input symbols corresponding to the encoded output symbol at different times. That is, as shown in Figure 5.

In an optional solution, at the transmitting end of the OvTDM system, the original input symbol sequence is waveform-encoded by using a waveform coding method to obtain a coded output symbol sequence, and the coded output symbol sequence is sent to the corresponding channel of the OvTDM system. At the receiving end, the receiving end can receive the received symbol sequence and know the corresponding state transition relationship.

Step S104, calculating a posterior log likelihood ratio of each original input symbol according to the received symbol sequence and the state transition relationship.

In an optional solution, the method of maximizing a posteriori probability (MAP) may be used according to the received symbol sequence and the state transition relationship, and the posterior log likelihood ratio of each original input symbol is calculated. That is, the soft information of the decoded output bits corresponding to each received symbol is obtained. As shown in FIG. 7, the soft information can be further applied to the SISO (soft-in soft-out) decoding structure, that is, the soft information is used as input information for the next iteration decoding, and the structure can help further improve the decoding success. Rate, reduce the bit error rate after decoding: Two decoders using the scheme of the present invention are constructed by interleaving and deinterleaving according to the structure of FIG.

It should be noted here that the OvTDM system via this decoding method can be widely used in practical wireless communication systems, such as various types of mobile communication systems, satellite communication, microwave line-of-sight communication, scatter communication, atmospheric optical communication, infrared communication and In any wireless communication system such as aquatic communication. It can be applied to both large-capacity wireless transmissions and small-capacity lightweight radio systems.

According to the above embodiment of the present invention, the received symbol sequence and the state transition relationship can be acquired, and the posterior log likelihood ratio of each original input symbol is calculated according to the received symbol sequence and the state transition relationship, so that the decoding is completed after the decoding is completed. The bit error probability is the smallest, and the soft information of the relevant bit is output, that is, the log likelihood ratio, which solves the technical problem that the hard decoding decision method is used in the prior art, and the soft information of each bit cannot be output. Therefore, by using the solution provided by the foregoing embodiment of the present invention, the obtained log likelihood ratio can be used as the SISO (soft-in soft-out) decoding algorithm of the OvXDM system, thereby improving the success rate of decoding and reducing the decoded Bit error rate.

Optionally, in the foregoing embodiment of the present invention, in step S104, the posterior log likelihood ratio of each original input symbol is calculated according to the received symbol sequence and the state transition relationship, including:

Step S112, calculating a posterior probability of each original input symbol according to the received symbol sequence and the state transition relationship.

In an optional solution, it can be assumed that the state of a certain path on the Trellis diagram shown in FIG. 6 at time m and time m-1 is respectively S _m and S _m-1 , corresponding to the state transition. The original input symbol is x _m , and the corresponding encoded output symbol of the corresponding OvTDM system is y _m . The received symbol sequence is r and the length is N.

Representing the sequence represented by the ath bit to the bth bit in the received symbol sequence, the overlap multiplexing coefficient of the OvTDM system is K, and the posterior probability p(x _m =±) of each original input symbol x _m can be calculated by the following formula 1|r):

Where x _m = +1 indicates that the original input symbol is +1, and x _m = -1 indicates that the original input symbol is -1.

Step S114, taking a log likelihood ratio for the posterior probability of each original input symbol, and obtaining a posterior log likelihood ratio of each original input symbol.

In an alternative, after obtaining the posterior probability p(x _m =±1|r) of each original input symbol x _m , the log likelihood ratio can be taken as the L _{app for the} posterior probability. (x _m ), it can be expressed as:

Step S116, calculating a current state transition parameter of each original input symbol, a forward recursive parameter of each original input symbol, and a backward recursive parameter of each original input symbol according to the received symbol sequence and the state transition relationship.

In an alternative scheme, the key to solving the log likelihood ratio of the posterior probability is that the joint probability p(x _m = +1, r) and p (x _m = -1) are solved by the above formula. r). Let U ⁺ and U ^- respectively represent the state transition relationship of the original input symbols x _m = +1 and x _m = -1 corresponding to the current state transition. According to the correlation properties of Bayes and Markov, the joint probability can be expressed. for:

Similarly, it is available

The forward recursive parameters of each original input symbol can be defined separately

Current state transition parameter

And the backward recursion parameter is

Then the above expression of joint probability can be simplified as:

Step S118, calculating a posterior logarithm of each original input symbol according to a current state transition parameter of each original input symbol, a forward recursive parameter of each original input symbol, and a backward recursive parameter of each original input symbol. Rather than.

Alternatively, in the above embodiment of the present invention, the posterior log likelihood ratio L _app (x _m ) of each original input symbol x _m can be calculated by the following formula:

Where γ _m (S _m-1 , S _m ) is the current state transition parameter of the original input symbol x _m , α _m (S _m-1 ) is the forward recursive parameter of the original input symbol x _m , β _m (S _m ) is the original input to the recursive parameter symbol X _m, S _m of the original input symbols X _m in the state of the current time point m, S _m-1 X _m input symbols into the original state of a previous time point m-1, U ⁺ For the state transition relationship where the original input symbol is x _m = +1, U ^- is the state transition relationship where the original input symbol is x _m = -1.

In an alternative, the forward recursive parameter α _m (S _m-1 ) of each original input symbol x _m is obtained, the current state transition parameter γ _m (S _m-1 , S _m ), backward After the recursive parameter β _m (S _m ), it can be substituted into the simplified formula of the joint probability, and finally the posterior log likelihood ratio L _app (x _m ) of each original input symbol x _m is obtained:

Optionally, in the foregoing embodiment of the present invention, in step S116, according to the received symbol sequence and the state transition relationship, a current state transition parameter of each original input symbol is calculated, and each of the original input symbols has a forward recursive parameter and each The backward recursive parameters of the original input symbol, including:

Step S122, acquiring a prior probability of each original input symbol and a channel condition transition probability in the current state.

Specifically, the prior probability of each of the original input symbols described above may be obtained in advance after being encoded at the system transmitting end. The channel condition transition probability in the current state can be obtained by establishing a channel model before decoding at the receiving end.

In an alternative, it can be assumed that the input a priori information is also expressed by the log likelihood ratio, and is set to L _a (x _m ).

Further obtaining the prior probability of the original input symbol,

It can be determined according to the channel characteristics. If the channel is assumed to be an AWGN channel, the channel condition transition probability p(r _m |y _m ) in the current state can be expressed as

Step S124: Obtain a current state transition parameter of each original input symbol according to a prior probability of each original input symbol and a channel condition transition probability in a current state.

Alternatively, in the above embodiment of the present invention, the current state transition parameter γ _m (S _m-1 , S _m ) of each original input symbol x _m may be calculated by the following formula:

Where p(x _m ) represents the prior probability of the original input symbol x _m and p(r _m |y _m ) is the channel condition transition probability in the current state.

In an alternative, γ _m (S _m-1 , S _m ) of the current parameter can be expressed as:

Therefore, the current state transition parameter of each original input symbol can be obtained according to the prior probability of each original input symbol and the channel condition transition probability in the current state.

Step S126, according to the current state transition parameter of each original input symbol, the forward recursive parameter of each original input symbol is obtained by forward recursion.

Alternatively, in the above embodiment of the present invention, the forward recursive parameter α _m (S _m-1 ) of each original input symbol x _m can be calculated by the following formula:

Where α _m-1 (S _m-2 ) is the forward recursive parameter of the previous moment.

Step S128, according to the current state transition parameter of each original input symbol, the backward recursive parameter of each original input symbol is obtained by backward recursion.

Alternatively, in the above embodiment of the present invention, the backward recursive parameter β _m (S _m ) of each symbol x _m can be calculated by the following formula:

Where β _m+1 (S _m+1 ) is the backward recursive parameter of the latter moment.

In an alternative approach, α _m (S _m-1 ) and β _m (S _m ) can be derived from forward recursion and backward recursion, respectively:

It should be noted here that in the actual calculation, since the forward recursive parameter and the backward recursive parameter are more likely to overflow after the number of recursive times, the algorithm is unstable, and therefore, it can be forwarded in each state calculation. Recursive and backward recursive parameters are scaled to

Optionally, in the foregoing embodiment of the present invention, in step S122, the channel condition transition probability in the current state is obtained, including:

Step S130: Establish a corresponding channel model according to channel characteristics of the channel corresponding to the overlapping multiplexing system, and obtain a channel condition transition probability in the current state.

In an optional solution, multiple channel models are pre-established at the receiving end. After receiving the received symbol sequence sent by the transmitting end, the corresponding channel model may be first selected according to the current channel characteristics to obtain a channel condition transition probability. In another optional solution, after receiving the received symbol sequence sent by the transmitting end, the receiving end may establish a corresponding channel model according to the channel characteristics of the current channel, thereby obtaining a channel condition transition probability in the current state.

Optionally, in the foregoing embodiment of the present invention, in step S116, a current state transition parameter of each original input symbol, a forward recursive parameter of each original input symbol, and a backward recursive parameter of each original input symbol are calculated. After that, the above methods include:

Step S142, transferring the current state of each original input symbol to the forward direction of each original input symbol. The recursive parameters and the backward recursive parameters of each original input symbol are computed in the logarithmic domain to obtain the logarithmic value of the current state transition parameter of each original input symbol, the logarithmic value of each forward recursive parameter of each original input symbol and each The logarithmic value of the backward recursive parameter of the original input symbol.

Step S144, calculating a logarithmic value of the current state transition parameter of each original input symbol, a logarithmic value of the forward recursive parameter of each original input symbol, and a logarithmic value of the backward recursive parameter of each original input symbol, and calculating each The posterior log likelihood ratio of the original input symbol.

It should be noted here that, as can be seen from the above algorithm, a large number of multiplication operations are involved in the algorithm, which is high in complexity and consumes a large amount of resources. Therefore, the partial multiplication operation involved in the a posteriori log likelihood ratio calculation process can be logarithmically converted into an addition operation.

In an optional solution, the logarithm of the forward recursive parameter, the backward recursive parameter and the current state transition parameter of each original input symbol may be performed to obtain a current state transition parameter of each original input symbol. The logarithm value log γ _m (S _m-1 , S _m ), the logarithm value of the forward recursive parameter of each original input symbol log α _m (S _m-1 ) and the logarithmic value of the backward recursive parameter of each original input symbol log β _m (S _m ):

Finally, the posterior log likelihood ratio L _app (x _m ) of each original input symbol can be rewritten as:

It should be noted here that according to the Jacobian Logarithm logarithmic formula, the original addition in the log domain can be converted to ln(e ^a +e ^b )=max(a,b)+ln(1+exp(-|ab|) ), where ln(1+exp(-|ab|)) represents a correction function. In the actual calculation process, if the correction function ln(1+exp(-|ab|)) needs to be calculated and the complexity of the calculation is avoided, the value of the correction function can usually be obtained by looking up the table. When the difference between a and b is large, the value of this correction function is very small and can be considered to be much smaller than max(a, b). At this point, the addition of the log field can also be approximated to take the maximum value, which is ln(e ^a +e ^b )≈max(a,b). This can further reduce the complexity of the decoding algorithm while the system is decoding. Using this method, all the operations related to the addition of the log domain described in the above section can be further simplified, and will not be further described herein.

It should also be noted here that the Trellis diagram shown in FIG. 6 shows that the main difference between the Trellis diagram and the conventional convolutional code is in the transition state of the head and the tail. Due to the difference in state number and state output, the transition state of the head and tail cannot be decoded using the same state list and method. At the same time, the transition state of the head and tail is closely related to the decoding accuracy of the head and tail. Therefore, in order to ensure the integrity of the decoded data and the decoding accuracy, it is necessary to separately process the received symbols of the header and trailer of the received symbol sequence.

Optionally, in the foregoing embodiment of the present invention, in step S104, before the a posteriori log likelihood ratio of each original input symbol is calculated according to the received symbol sequence and the state transition relationship, the method further includes:

Step S152, acquiring the number of overlapping multiplexing K and the length L of the original input symbol sequence, wherein the original input symbol sequence comprises: a plurality of original input symbols.

Specifically, the length of the original input symbol sequence may be the number of original input symbols in the original input symbol sequence.

Step S154: Determine whether any one of the received symbols is the first K received symbols in the received symbol sequence, or whether any one of the received symbols is the last K received symbols in the received symbol sequence.

Step S156, if any one of the received symbols is not the first K received symbols in the received symbol sequence, and any one of the received symbols is not the Lth received symbol in the received symbol sequence, then any original is calculated according to the received symbol sequence and the state transition relationship. Enter the posterior log likelihood ratio of the symbol.

In an optional solution, the transmitting end convolutionally encodes the original input symbol sequence, and for the OvTDM system with the overlapping multiplexing number K, the length of the encoded output symbol sequence obtained after encoding is N=L+K-1, The first K received symbols are the transition state of the head, and the last K received symbols are the transition state of the tail. Before the receiving end decodes the received symbol sequence, it is determined whether the currently processed received symbol is a received symbol of the header or a received symbol of the tail, and if the received symbol is neither a received symbol of the header nor a received symbol of the tail, Then, according to the above scheme, the posterior log likelihood ratio of the original input symbol is calculated according to the received symbol sequence and the state transition relationship.

Optionally, in the foregoing embodiment of the present invention, in the case that any one of the received symbols is the first K received symbols in the received symbol sequence, the method further includes:

Step S162: Acquire a first state transition relationship from the state transition relationship according to the number of overlapping multiplexes K, where the first state transition relationship includes: the first K state transitions in the state transition relationship.

Step S164, establishing a corresponding state transition list according to the first state transition relationship.

Step S166, calculating a posterior log likelihood ratio of any one of the original input symbols according to any one of the received symbols and the state transition list.

It should be noted here that from the Trellis diagram shown in FIG. 6, the header state includes data input, and the difference from the intermediate state exists only in the state number and the state output. And the transition of the head state constitutes a tree diagram which can be equivalent to one, that is, the state of each t time only corresponds to the state of one t-1 time, thereby simplifying the head state transition relationship. Therefore, the head state only needs to establish a corresponding state transition relationship for calculation.

In an alternative, if the currently processed received symbols are the first K received symbols, ie, the received symbols of the header, the first K state transitions, ie, the header states, may be obtained from the state transition relationship. According to the state of the head, a state transition list is separately established, and the forward recursive parameter, the backward recursive parameter and the current state transition parameter are calculated, thereby calculating the posterior log likelihood ratio:

Optionally, in the foregoing embodiment of the present invention, in the case that any one of the received symbols is the K symbols in the received symbol sequence, the method further includes:

Step S172: Obtain a backward recursive parameter of the Lth original input symbol.

Step S174, calculating a posterior log likelihood ratio of the Lth original input symbol according to the Lth original input symbol, the backward recursive parameter and the state transition relationship.

It should be noted here that, from the Trellis diagram shown in FIG. 6, the transition state of the tail is different from that of the head, and there is no corresponding data input in the transition state of the tail, and the tail transition state is only related to the backward recursive variable β _{m .} (S _m ) related. If the input sequence length is L, in the tail decoding, the backward recursive variable of the Lth bit only needs to be calculated through the tail transition state, and the posterior log likelihood ratio after the L bit does not need to be calculated.

In an optional solution, if the currently processed received symbol is the last K received symbols, that is, the received symbols at the tail, the backward recursive parameter β _{L of} the Lth bit can be directly calculated according to the independence of the Gaussian noise sequence. (S _L ),

And obtaining a current state transition parameter of the original input symbol according to the prior probability of the original input symbol and a channel condition transition probability in the current state, and obtaining a forward recursive parameter of the original input symbol by forward recursion, thereby finally The posterior likelihood ratio of the original input symbol is obtained.

Example 2

In accordance with an embodiment of the present invention, an apparatus embodiment of a decoding apparatus of an overlay multiplexing system is also provided.

FIG. 8 is a schematic diagram of a decoding apparatus of an overlap multiplexing system according to an embodiment of the present invention. As shown in FIG. 8, the apparatus includes the following modules:

The obtaining module 71 is configured to obtain a received symbol sequence and a state transition relationship, where the received symbol sequence includes: a plurality of received symbols, where the plurality of received symbols are encoded by the overlapping multiplexing system, and are obtained after channel transmission. The state transition relationship includes: a state transition relationship corresponding to the coded output symbol at different times of different original input symbols.

Optionally, in the embodiment of the present invention, the OvTDM system is taken as an example for description, and other OvXDM systems can be similarly used. As shown in Figure 3, the OvTDM system is a waveform convolutional coding system, so there is no way to use traditional symbol-by-symbol detection when decoding. Figure 4 shows the input and output relationship tree diagram of the OvTDM system with binary (+1,-1) data at K=3. The figure depicts the data transfer status of the OvTDM system, and it can also be very Clearly discover the node transfer relationship diagram of the OvTDM system, as shown in Figure 5. Therefore, the input-output relationship of the OvTDM system can be represented by a Trellis diagram, as shown in Figure 6.

The calculating module 73 is configured to calculate a posterior log likelihood ratio of each original input symbol according to the received symbol sequence and the state transition relationship.

In an optional solution, the method of maximizing a posteriori probability (MAP) may be used according to the received symbol sequence and the state transition relationship, and the posterior log likelihood ratio of each original input symbol is calculated. That is, the soft information of the decoded output bits corresponding to each received symbol is obtained. As shown in FIG. 7, the soft information can be further applied to the SISO (soft-in soft-out) decoding structure, that is, the soft information is used as input information for the next iteration decoding, and the structure can help further improve the decoding success. Rate, reduce the bit error rate after decoding.

The serial numbers of the embodiments of the present invention are merely for the description, and do not represent the advantages and disadvantages of the embodiments.

In the above-mentioned embodiments of the present invention, the descriptions of the various embodiments are different, and the parts that are not detailed in a certain embodiment can be referred to the related descriptions of other embodiments.

In the several embodiments provided by the present application, it should be understood that the disclosed technical contents may be implemented in other manners. The device embodiments described above are only schematic. For example, the division of the unit may be a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, unit or module, and may be electrical or otherwise.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: a U disk, a read only memory (ROM, Read-Only) Memory, random access memory (RAM), removable hard disk, disk or optical disk, and other media that can store program code.

The above description is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can also make several improvements and retouchings without departing from the principles of the present invention. It should be considered as the scope of protection of the present invention.

Claims

A decoding method for an overlapping multiplexing system, comprising:

Obtaining a received symbol sequence and a state transition relationship, where the received symbol sequence includes: a plurality of received symbols, where the plurality of received symbols are encoded by an overlapping multiplexing system and transmitted through a channel, The state transition relationship includes: a state transition relationship corresponding to the coded output symbol at different time points of different original input symbols;

A posteriori log likelihood ratio of each original input symbol is calculated based on the received symbol sequence and the state transition relationship.
The method according to claim 1, wherein the posterior log likelihood ratio of each of the original input symbols is calculated according to the received symbol sequence and the state transition relationship, including:

Calculating a posterior probability of each of the original input symbols according to the received symbol sequence and the state transition relationship;

A log likelihood ratio is obtained for the posterior probability of each of the original input symbols, and a posterior log likelihood ratio of each of the original input symbols is obtained.
The method according to claim 2, wherein calculating a posteriori log likelihood ratio of each of the original input symbols according to the received symbol sequence and the state transition relationship comprises:

Calculating a current state transition parameter of each of the original input symbols according to the received symbol sequence and the state transition relationship, a forward recursive parameter of each of the original input symbols, and a back of each of the original input symbols Recursive parameter

Calculating a forward recursive parameter of each of the original input symbols and a backward recursive parameter of each of the original input symbols according to a current state transition parameter of each of the original input symbols, and calculating each of the original input symbols A posteriori log likelihood ratio.
The method according to claim 3, wherein the posterior log likelihood ratio L app (x m ) of each of the original input symbols x m is calculated by the following formula:

Where γ m (S m-1 , S m ) is the current state transition parameter of the original input symbol x m , α m (S m-1 ) is the forward recursive parameter of the original input symbol x m , β m (S m ) of the original input symbol x m is the original input to the recursive parameter symbol x m, S m in the state at the current time, S m-1 x m is the original input symbols a previous state of the time, U + for the original input symbol For a state transition relationship of x m = +1, U - is a state transition relationship where the original input symbol is x m = -1.
The method according to claim 3, wherein a current state transition parameter of each of the original input symbols is calculated according to the received symbol sequence and the state transition relationship, and the front of each of the original input symbols To the recursive parameters and the backward recursive parameters of each of the original input symbols, including:

Obtaining a prior probability of each of the original input symbols and a channel condition transition probability in a current state;

Obtaining a current state transition parameter of each of the original input symbols according to a prior probability of each of the original input symbols and a channel condition transition probability in the current state;

Obtaining a forward recursive parameter of each of the original input symbols by forward recursion according to a current state transition parameter of each of the original input symbols;

The backward recursive parameters of each of the original input symbols are obtained by backward recursion according to the current state transition parameters of each of the original input symbols.
The method according to claim 5, characterized in that the current state transition parameter γ m (S m-1 , S m ) of each of the original input symbols x m is calculated by the following formula:

Where p(x m ) represents the prior probability of the original input symbol x m , and p(r m |y m ) is the channel condition transition probability in the current state.
The method according to claim 5, characterized in that the forward recursive parameter α m (S m-1 ) of each of the original input symbols x m is calculated by the following formula:

Where α m-1 (S m-2 ) is the forward recursive parameter of the previous moment.
The method according to claim 5, characterized in that the backward recursive parameter β m (S m ) of each of the original input symbols x m is calculated by the following formula:

Where β m+1 (S m+1 ) is the backward recursive parameter of the latter moment.
The method according to claim 5, wherein the channel condition transition probability in the current state is obtained, include:

And establishing a corresponding channel model according to channel characteristics of the channel corresponding to the overlapping multiplexing system, to obtain a channel condition transition probability in the current state.
A method according to any one of claims 3 to 9, wherein a current state transition parameter of each of the original input symbols is calculated, a forward recursive parameter of each of the original input symbols, and said After each backward recursive parameter of the original input symbol, the method includes:

Converting a current state transition parameter of each of the original input symbols, a forward recursive parameter of each of the original input symbols, and a backward recursive parameter of each of the original input symbols in a logarithmic domain to obtain the each a logarithmic value of the current state transition parameter of the original input symbol, a logarithmic value of the forward recursive parameter of each of the original input symbols, and a logarithmic value of the backward recursive parameter of each of the original input symbols;

Calculating a logarithmic value of a current state transition parameter of each of the original input symbols, a logarithmic value of the forward recursive parameter of each of the original input symbols, and a logarithmic value of the backward recursive parameter of each of the original input symbols A posteriori log likelihood ratio for each of the original input symbols is obtained.
The method of claim 1 wherein said method further comprises calculating a posterior log likelihood ratio of said each original input symbol based on said received symbol sequence and said state transition relationship include:

Obtaining an overlap multiplexing number K and a length L of the original input symbol, wherein the original input symbol comprises: the plurality of original input symbols;

Determining whether any one of the received symbols is the first K received symbols in the received symbol sequence, or whether any one of the symbols is the last K received symbols in the received symbol sequence;

And if the any one received symbol is not the first K received symbols in the received symbol sequence, and the any one received symbol is not the last K received symbols in the received symbol sequence, according to the received symbol sequence and the The state transition relationship calculates the posterior log likelihood ratio of any one of the original input symbols.
The method according to claim 11, wherein in the case that any one of the received symbols is the first K received symbols in the received symbol sequence, the method further comprises:

Acquiring, according to the number of overlapping multiplexes K, a first state transition relationship from the state transition relationship, where the first state transition relationship includes: a first K state transitions in the state transition relationship;

Establishing a corresponding state transition list according to the first state transition relationship;

Calculating the arbitrary one according to any one of the received symbols and the state transition list The a posteriori log likelihood ratio of the input symbol is entered.
The method according to claim 11, wherein in the case that any one of the received symbols is the last K received symbols in the received symbol sequence, the method further comprises:

Obtaining a backward recursive parameter of the Lth original input symbol;

And determining, according to the Lth original input symbol, the backward recursive parameter and the state transition relationship, a posterior log likelihood ratio of the Lth original input symbol.
A decoding device for an overlay multiplexing system, comprising:

And an acquiring module, configured to acquire a received symbol sequence and a state transition relationship, where the received symbol sequence includes: a plurality of received symbols, where the plurality of original input symbols are encoded by an overlapping multiplexing system and pass through a channel After the transmission, the state transition relationship includes: a state transition relationship corresponding to the coded output symbol at different time points of different original input symbols;

And a calculating module, configured to calculate a posterior log likelihood ratio of each original input symbol according to the received symbol sequence and the state transition relationship.