A decoding method, device and storage medium
By obtaining the log-likelihood ratio of bit combinations and prior knowledge, and using Markov processes to determine the posterior probability, the problem of unrecoverable distorted bit streams in existing technologies is solved, and accurate decoding in noisy environments is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA UNITED NETWORK COMM GRP CO LTD
- Filing Date
- 2023-08-03
- Publication Date
- 2026-06-05
AI Technical Summary
In existing technologies, error concealment techniques and hard-decision decoding cannot effectively recover distorted bitstreams, resulting in the inability to accurately decode the information transmitted by the bitstream.
By obtaining the log-likelihood ratio, channel transition probability, and prior probability of the current bit combination, the posterior probability is determined using a Markov process, and the decoding result is determined using a soft-decision decoding method.
It enables accurate decoding of bitstreams in noisy environments, improving the accuracy and reliability of information recovery.
Smart Images
Figure CN116961837B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of communication technology, and in particular to a decoding method, apparatus and storage medium. Background Technology
[0002] In digital communication, the signals used to transmit information are encoded into a bitstream at the transmitting end, and at the receiving end, the bitstream is decoded to obtain the information transmitted by the signal. However, noise and other factors may exist in the channel through which the bitstream is transmitted, affecting its transmission. Under the influence of noise, the bitstream transmitted in the channel may be distorted, causing the receiving end to be unable to correctly decode the information to be transmitted.
[0003] Currently, error concealment techniques and hard-decision decoding are commonly used to decode received bitstreams. However, neither error concealment nor hard-decision decoding can recover distorted bitstreams. Therefore, when bitstreams are distorted, neither method can accurately decode the information transmitted by the bitstream. Summary of the Invention
[0004] This application provides a decoding method, apparatus, and storage medium to solve the technical problem of how to decode distorted bitstreams in the prior art.
[0005] To achieve the above objectives, this application adopts the following technical solution:
[0006] In a first aspect, a decoding method is provided, comprising: acquiring a current bit combination; the current bit combination including at least one bit; determining the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination; determining the prior probability of the current bit combination based on prior knowledge corresponding to the current bit combination; the prior knowledge including bit information of received historical bit combinations; determining the posterior probability of the current bit combination based on the channel transition probability and the prior probability; determining the decoding result based on the posterior probability of the current bit combination; the decoding result including target decoding parameters.
[0007] Optionally, the channel transition probability of the current bit combination is determined based on the log-likelihood ratio of each bit in the current bit combination, including: determining the bit error rate of each bit in the current bit combination based on the log-likelihood ratio of each bit in the current bit combination; determining the channel transition probability of each bit in the current bit combination based on the bit error rate of each bit in the current bit combination; and determining the channel transition probability of the current bit combination as the product of the channel transition probabilities of multiple bits in the current bit combination.
[0008] Optionally, the prior probability of the current bit combination can be determined based on the prior knowledge corresponding to the current bit combination, including: processing the prior knowledge based on an Nth-order Markov process to obtain the prior probability of the current bit combination.
[0009] Optionally, the current bit combination corresponds to multiple candidate bit combinations; the number of posterior probabilities of the current bit combination is multiple; one posterior probability corresponds to one candidate bit combination; the decoding result is determined based on the posterior probability of the current bit combination, including: selecting a target posterior probability greater than a preset threshold from the multiple posterior probabilities, and determining the decoding parameters of the candidate bit combination corresponding to the target posterior probability as the decoding result; or, determining the decoding result by summing the products of the posterior probability of each candidate bit combination and the decoding parameters of each candidate bit combination.
[0010] In a second aspect, a decoding apparatus is provided, comprising: an acquisition unit and a determination unit; the acquisition unit is configured to acquire a current bit combination; the current bit combination includes at least one bit; the determination unit is configured to determine the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination; the determination unit is further configured to determine the prior probability of the current bit combination based on prior knowledge corresponding to the current bit combination; the prior knowledge includes bit information of received historical bit combinations; the determination unit is further configured to determine the posterior probability of the current bit combination based on the channel transition probability and the prior probability; the determination unit is further configured to determine a decoding result based on the posterior probability of the current bit combination; the decoding result includes target decoding parameters.
[0011] Optionally, the determining unit is specifically used for: determining the bit error rate of each bit in the current bit combination based on the log-likelihood ratio of each bit in the current bit combination; determining the channel transition probability of each bit in the current bit combination based on the bit error rate of each bit in the current bit combination; and determining the channel transition probability of the current bit combination as the product of the channel transition probabilities of multiple bits in the current bit combination.
[0012] Optionally, a determining unit is specifically used to: process prior knowledge based on an Nth-order Markov process to obtain the prior probability of the current bit combination.
[0013] Optionally, the current bit combination corresponds to multiple candidate bit combinations; the number of posterior probabilities of the current bit combination is multiple; one posterior probability should correspond to one candidate bit combination; the determining unit is specifically used for: selecting a target posterior probability greater than a preset threshold from the multiple posterior probabilities, and determining the decoding parameters of the candidate bit combination corresponding to the target posterior probability as the decoding result; and determining the sum of the products of the posterior probability of each candidate bit combination and the decoding parameters of each candidate bit combination as the decoding result.
[0014] Thirdly, a decoding device is provided, including a memory and a processor; the memory is used to store computer execution instructions, and the processor is connected to the memory via a bus; when the decoding device is running, the processor executes the computer execution instructions stored in the memory to cause the decoding device to perform the decoding method described in the first aspect.
[0015] The decoding device can be a network device or a component of a network device, such as a chip system within the network device. The chip system supports the network device in implementing the functions involved in the first aspect and any of its possible implementations, such as acquiring, determining, and transmitting the data and / or information involved in the aforementioned decoding method. The chip system includes a chip, but may also include other discrete devices or circuit structures.
[0016] Fourthly, a computer-readable storage medium is provided, comprising computer-executable instructions that, when executed on a computer, cause the computer to perform the decoding method described in the first aspect.
[0017] Fifthly, a computer program product is also provided, which includes computer instructions that, when executed on a decoding device, cause the decoding device to perform the decoding method as described in the first aspect above.
[0018] It should be noted that the aforementioned computer instructions may be stored, in whole or in part, on a computer-readable storage medium. This computer-readable storage medium may be packaged together with the processor of the decoding device, or it may be packaged separately from the processor of the decoding device; this application does not limit this.
[0019] The descriptions of the second, third, fourth, and fifth aspects of this application can be referenced to the detailed description of the first aspect.
[0020] In the embodiments of this application, the names of the aforementioned decoding devices do not limit the devices or functional modules themselves. In actual implementation, these devices or functional modules may appear under other names. For example, the receiving unit may also be called a receiving module, receiver, etc. As long as the functions of each device or functional module are similar to those of this application, they fall within the scope of the claims of this application and their equivalents.
[0021] The technical solution provided in this application brings at least the following beneficial effects:
[0022] Based on any of the foregoing aspects, this application provides a decoding method, comprising: acquiring a current bit combination, wherein the current bit combination includes at least one bit; then, determining the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination; next, determining the prior probability of the current bit combination based on prior knowledge corresponding to the current bit combination, wherein the prior knowledge includes bit information of received historical bit combinations; then, determining the posterior probability of the current bit combination based on the channel transition probability and the prior probability; subsequently, determining the decoding result based on the posterior probability of the current bit combination; the decoding result includes target decoding parameters.
[0023] As shown above, the electronic device can determine the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination. Next, the electronic device can determine the prior probability of the current bit combination based on the prior knowledge corresponding to the current bit combination. Then, the electronic device can determine the posterior probability of the current bit combination based on the channel transition probability and the prior probability. Since the posterior probability can represent the probability of the actual transmitted bit combination, the electronic device can determine the target decoding parameters in the decoding result using the posterior probability of the current bit combination.
[0024] The beneficial effects of the first, second, third, fourth, and fifth aspects of this application can all be referred to in the analysis of the above-mentioned beneficial effects, and will not be repeated here. Attached Figure Description
[0025] Figure 1 This is a schematic diagram of the structure of a decoding system provided in an embodiment of this application;
[0026] Figure 2 This is a schematic diagram of the hardware structure of a decoding device provided in an embodiment of this application;
[0027] Figure 3 A flowchart illustrating a decoding method provided in this application embodiment. Figure 1 ;
[0028] Figure 4 A flowchart illustrating a decoding method provided in this application embodiment. Figure 2 ;
[0029] Figure 5 A flowchart illustrating a decoding method provided in this application embodiment. Figure 3 ;
[0030] Figure 6 This application provides a schematic diagram of decoding based on posterior probability in an embodiment of the present application.
[0031] Figure 7 A flowchart illustrating a decoding method provided in this application embodiment. Figure 4 ;
[0032] Figure 8 This is a schematic diagram of a decoding device provided in an embodiment of this application. Detailed Implementation
[0033] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0034] It should be noted that in the embodiments of this application, the words "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.
[0035] To facilitate a clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish the same or similar items with essentially the same function and effect. Those skilled in the art can understand that the terms "first" and "second" are not intended to limit the quantity or execution order.
[0036] As described in the background section, in digital communication, the signal used to transmit information is encoded into a bit stream at the transmitting end, and at the receiving end, the bit stream is decoded to obtain the information transmitted by the signal. However, noise and other factors may exist in the channel through which the bit stream is transmitted, affecting its transmission. Under the influence of noise, the bit stream transmitted in the channel may be distorted, causing the receiving end to be unable to correctly decode the information to be transmitted.
[0037] Currently, error concealment techniques and hard-decision decoding are commonly used to decode received bitstreams. However, neither error concealment nor hard-decision decoding can recover distorted bitstreams. Therefore, when bitstreams are distorted, neither method can accurately decode the information transmitted by the bitstream.
[0038] To address the aforementioned problems, this application provides a decoding method, comprising: acquiring a current bit combination, wherein the current bit combination includes at least one bit; determining the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination; determining the prior probability of the current bit combination based on prior knowledge corresponding to the current bit combination, wherein the prior knowledge includes bit information of received historical bit combinations; determining the posterior probability of the current bit combination based on the channel transition probability and the prior probability; and finally determining the decoding result based on the posterior probability of the current bit combination. The decoding result includes target decoding parameters.
[0039] As shown above, the electronic device can determine the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination. Next, the electronic device can determine the prior probability of the current bit combination based on the prior knowledge corresponding to the current bit combination. Then, the electronic device can determine the posterior probability of the current bit combination based on the channel transition probability and the prior probability. Since the posterior probability can represent the probability of the actual transmitted bit combination, the electronic device can determine the target decoding parameters in the decoding result using the posterior probability of the current bit combination.
[0040] This decoding method is applicable to decoding systems. Figure 1 One structure of the decoding system is shown. For example... Figure 1 As shown, the decoding system includes a data transmission device 101 and an electronic device 102.
[0041] The data transmitting device 101 and the electronic device 102 are connected in communication.
[0042] In this application, data transmitting device 101 is used to transmit bit combinations to electronic device 102. Electronic device 102 is used to receive the bit combinations transmitted by data transmitting device 101, and determine the posterior probability of the bit combinations based on the channel transition probability and prior probability of the bit combinations, so that electronic device 102 can determine the target decoding parameters through the posterior probability of the bit combinations. Subsequently, electronic device 102 is also used to decode the bit combinations through the target decoding parameters.
[0043] Optionally, the data transmitting device 101 may also encode the information to be transmitted into a combination of bits.
[0044] Optionally, the information transmitted by the bit combination can be voice information, video information, or other types of information, and this application embodiment does not limit this.
[0045] The data transmission device 101 and the electronic device 102 can be terminals, servers, or other types of electronic devices, and this application embodiment does not limit them.
[0046] Optionally, the aforementioned terminal may be a device that provides voice and / or data connectivity to a user, a handheld device with wireless connectivity, or other processing device connected to a wireless modem. The terminal may communicate with one or more core networks via a radio access network (RAN). The terminal may be a mobile terminal, such as a mobile phone (or "cellular" phone) and a computer with a mobile terminal, or a portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile device that exchanges voice and / or data with the radio access network, such as a mobile phone, tablet computer, laptop computer, netbook, or personal digital assistant (PDA).
[0047] The aforementioned server can be one of the servers in a server cluster (composed of multiple servers), a chip in the server, a system-on-a-chip in the server, or a virtual machine (VM) deployed on a physical machine. This application does not limit the specific implementation of the server.
[0048] The basic hardware structure of electronic device 102 includes Figure 2 The decoding device shown includes the following components. Figure 2 Taking the decoding device shown as an example, the hardware structure of electronic device 102 will be introduced.
[0049] like Figure 2 The diagram shown is a hardware structure schematic of a decoding device provided in an embodiment of this application. The decoding device includes a processor 21, a memory 22, a communication interface 23, and a bus 24. The processor 21, the memory 22, and the communication interface 23 are connected via the bus 24.
[0050] Processor 21 is the control center of the decoding device. It can be a single processor or a collective term for multiple processing elements. For example, processor 21 can be a general-purpose central processing unit (CPU) or other general-purpose processors. Among them, the general-purpose processor can be a microprocessor or any conventional processor.
[0051] As one embodiment, processor 21 may include one or more CPUs, for example Figure 2 CPU 0 and CPU 1 are shown in the diagram.
[0052] The memory 22 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.
[0053] In one possible implementation, the memory 22 can exist independently of the processor 21. The memory 22 can be connected to the processor 21 via a bus 24 and is used to store instructions or program code. When the processor 21 calls and executes the instructions or program code stored in the memory 22, it can implement the decoding method provided in the following embodiments of this application.
[0054] In this embodiment, the software programs stored in the memory 22 of the electronic device 102 are different, so the functions implemented by the electronic device 102 are different. The functions performed by each device will be described with reference to the following flowchart.
[0055] In another possible implementation, the memory 22 can also be integrated with the processor 21.
[0056] Communication interface 23 is used for the decoding device to connect with other devices via a communication network, such as Ethernet, wireless access network, or wireless local area network (WLAN). Communication interface 23 may include a receiving unit for receiving data and a transmitting unit for sending data.
[0057] Bus 24 can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 2 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.
[0058] It should be pointed out that, Figure 2 The structure shown does not constitute a limitation on the decoding device, except Figure 2 In addition to the components shown, the decoding device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.
[0059] The decoding method provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings.
[0060] The decoding method provided in this application embodiment is applied to Figure 1 The electronic device 102 in the decoding system shown, such as Figure 3 As shown, the decoding method provided in this application includes:
[0061] S301, The electronic device obtains the current bit combination.
[0062] The current bit combination includes at least one bit.
[0063] Specifically, during data transmission, the data transmitting device can encode the information to be transmitted into a bit stream. Then, the data transmitting device can send the current bit combination from the bit stream to the electronic device. Subsequently, in order to obtain the information sent by the data transmitting device, the electronic device can decode the received current bit combination to obtain the information sent by the data transmitting device.
[0064] Optionally, the information transmitted by the data transmitting device can be video information or audio information.
[0065] It should be understood that, since a bit is either 0 or 1, the current bit combination includes at least one bit 0 or bit 1.
[0066] It should be noted that the data transmitting device can quantize the information to be transmitted into target decoding parameters, and then encode the quantized target decoding parameters into bit combinations. In this case, a frame includes at least one bit combination. Furthermore, within a frame, one parameter corresponds to one bit combination.
[0067] For example, suppose the electronic device receives a current bit combination of 000. Because the bit stream will be distorted when transmitted in the channel, the actual bit combination sent by the data transmitting device may not be 000. In this case, there are eight possible bit combinations that the data transmitting device can send: 000, 001, 010, 100, 011, 110, 101, and 111.
[0068] S302. The electronic device determines the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination.
[0069] Optionally, the decoding method provided in this application embodiment can also be referred to as a soft-decision decoding method.
[0070] Soft-decision decoding determines the true bit of each bit by calculating the error probability of each bit (e.g., the log-likelihood ratio of each bit).
[0071] During soft-decision decoding, the electronic device can determine the log-likelihood ratio of each bit in the current bit combination. Then, the electronic device can determine the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination, so that the electronic device can determine the posterior probability of the current bit combination based on the channel transition probability.
[0072] The channel transition probability is used to represent the probability of an electronic device receiving a combination of bits given the possible combinations of bits that the data transmitting device may send.
[0073] It should be noted that electronic devices can obtain the received power E of the channel transmitting the bit stream. b And noise power N0, and the sign of each bit Next, the electronic device can determine the log-likelihood ratio of each bit in the current bit combination.
[0074]
[0075] Where m is the m-th bit in the current bit combination. The signal-to-noise ratio of the channel. It served a regularization function.
[0076] Due to the received power E in the same channel b Since the noise power N0 is constant, the log-likelihood ratio for each bit is proportional to the number of symbols received.
[0077] Next, the electronic device can determine the bit error rate (BER) of each bit based on the log-likelihood ratio of each bit in the current bit combination. Then, the electronic device can determine the channel transition probability of each bit based on the BER of each bit. Finally, the electronic device can determine the channel transition probability of the current bit combination as the product of the channel transition probabilities of multiple bits in the current bit combination.
[0078] For example, suppose the current bit combination received by the electronic device is (l represents the l-th frame received by the electronic device), the bit combination transmitted by the data transmitting device may be: (where i is the i-th possible bit combination that the data transmitting device may send), then the electronic device can determine the channel transition probability of the current bit combination as follows:
[0079] Optionally, the electronic device may execute S302 first and then S303, or it may execute S303 first and then S302, or it may execute S302 and S303 simultaneously. This application embodiment does not limit this.
[0080] S303. The electronic device determines the prior probability of the current bit combination based on the prior knowledge corresponding to the current bit combination.
[0081] Prior knowledge includes bit information from received historical bit combinations.
[0082] Specifically, since multiple frames are transmitted in the channel as bit streams, and to recover distorted frames, the data transmitting device adds redundancy (e.g., correlation between frames) between frames so that the electronic device can recover the distorted bit combinations through redundancy. Therefore, the electronic device can decode the current bit combination using prior knowledge. In this case, the electronic device acquires the prior knowledge corresponding to the current bit combination (i.e., the prior knowledge corresponding to the redundancy between the current frame and the previous N frames). Then, the electronic device can determine the prior probability of the current bit combination using the prior knowledge, so that the electronic device can determine the posterior probability of the current bit combination based on the prior probability.
[0083] Among them, prior probability, also known as predictive prior probability or predictive probability, represents the probability that the data transmitting device may transmit a combination of bits given the historical bit combinations received by the electronic device.
[0084] For example, suppose the current bit combination received by the electronic device is the bit combination of frame l, and the bit combination corresponding to the target decoding parameters received by the electronic device for frames 1, 2, ... l-1 is... (i.e., historical bit combinations in prior probability), the possible bit combinations that the data transmitting device may send are: Then the electronic device can determine the prior probability of the current bit combination as follows:
[0085] S304. The electronic device determines the posterior probability of the current bit combination based on the channel transition probability and the prior probability.
[0086] Specifically, after determining the channel transition probability and prior probability of the current bit, the electronic device can determine the posterior probability of the current bit combination based on the chain rule, the channel transition probability, and the prior probability, so that the electronic device can decode the current bit combination according to the posterior probability of the current bit combination.
[0087] The posterior probability of the current bit combination can be expressed as follows: In the received frames 1, 2…l, the received bit combinations are... In this case, the bit combination sent by the data transmitting device may be: The probability of.
[0088] According to the chain rule, the posterior probability of the current bit combination is... for:
[0089]
[0090] Where i represents the i-th possible bit combination that the data transmitting device may send, and l represents the l-th frame received by the electronic device (i.e., the current frame corresponding to the current bit combination). When the channel transmitting the bit combination is a memoryless channel, the posterior probability of the current bit combination can also be:
[0091]
[0092] in, It is a constant used to ensure (I represents I possible combinations of bits that the data transmitting device may send). In this way, the electronic device can determine... f represents the f-th bit combination that the data transmitting device may send in the l-th frame.
[0093] Since the channel transition probability of the current bit combination is The prior probability of the current bit combination is Electronic devices can then substitute the channel transition probability and prior probability into the formula. In this way, the posterior probability of the current bit combination can be obtained.
[0094] It should be noted that the channel used to transmit bit combinations can be a channel with memory or a channel without memory. In the embodiments of this application, since the distortion of one bit combination in a memoryless channel will not affect other bit combinations, the electronic device determines the channel for transmitting bit combinations as a memoryless channel when determining the posterior probability, regardless of whether the channel for transmitting bit combinations has memory or not.
[0095] For example, assuming the current bit combination is 000, the electronic device can determine the posterior probability of the current bit combination as P(000|000), P(001|000), P(010|000), P(100|000), P(011|000), P(110|000), P(101|000), P(111|000).
[0096] S305. The electronic device determines the decoding result based on the posterior probability of the current bit combination.
[0097] The decoding result includes the target decoding parameters.
[0098] Specifically, after determining the posterior probability of the current bit combination, the electronic device can determine the corresponding decoding result of the current bit combination using either the Minimum Mean Squared Error (MMSE) method or the Maximum a posteriori (MAP) method, thereby obtaining the target decoding parameters corresponding to the current bit combination. Then, the electronic device can decode the current bit combination according to the target decoding parameters to obtain the information to be transmitted corresponding to the current bit combination.
[0099] Since the data transmitting device may transmit multiple bit combinations, and different bit combinations correspond to different target decoding parameters, the electronic device can use the minimum mean square error method to determine the target decoding parameters corresponding to the current bit combination.
[0100] The specific implementation of the least mean square error method is as follows: Multiple target decoding parameters are determined corresponding to multiple bit combinations that the data transmitting device may transmit. Then, the electronic device can determine the target decoding parameter corresponding to the current bit combination by summing the products of the multiple target decoding parameters and the posterior probability corresponding to each target decoding parameter.
[0101] The specific implementation of the maximum a posteriori probability method is as follows: After determining multiple posterior probabilities, the electronic device can select the largest posterior probability among them. Then, the electronic device can determine the bit combination that the data transmitting device might send corresponding to the largest posterior probability as the actual bit combination to be sent. Next, the electronic device can determine the parameters corresponding to the actual bit combination to be the target decoding parameters.
[0102] It should be noted that the process by which electronic devices determine the target decoding parameters can also be called parameter estimation.
[0103] In some embodiments, combined with Figure 3 ,like Figure 4 As shown, in S302 above, the electronic device determines the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination, specifically including:
[0104] S401. The electronic device determines the bit error rate of each bit in the current bit combination based on the log-likelihood ratio of each bit in the current bit combination.
[0105] Specifically, after determining the log-likelihood ratio of each bit in the current bit combination, the electronic device can determine the bit error rate (BER) of each bit in the current bit combination based on the log-likelihood ratio of each bit combination in the current bit combination. l (m):
[0106]
[0107] Among them, BER l (m) represents the bit error rate of the m-th bit in the current bit combination in the l-th frame. It is the log-likelihood ratio of the m-th bit in the current bit combination.
[0108] S402. The electronic device determines the channel transition probability of each bit in the current bit combination based on the bit error rate of each bit in the current bit combination.
[0109] Specifically, the electronic device can determine the channel transition probability of each bit in the current bit combination based on the bit error rate of each bit in the current bit combination.
[0110]
[0111] in, It is the m-th bit in the current bit combination in the l-th frame. It is the m-th bit in the i-th bit combination in the l-th frame that the data transmitting device may transmit.
[0112] S403. The electronic device determines the channel transition probability of the current bit combination as the product of the channel transition probabilities of multiple bits in the current bit combination.
[0113] Specifically, after determining the channel transition probabilities of multiple bits in the current bit combination, the electronic device can determine the channel transition probability of the current bit combination as the product of the channel transition probabilities of the multiple bits in the current bit combination.
[0114]
[0115] Where m represents the m-th bit in the current bit combination, and M represents the presence of M bits in the current bit combination.
[0116] In some embodiments, combined with Figure 4 ,like Figure 5 As shown, in S303 above, the electronic device determines the prior probability of the current bit combination based on the prior knowledge corresponding to the current bit combination, specifically including:
[0117] S501. The electronic device processes prior knowledge based on an Nth-order Markov process to obtain the prior probability of the current bit combination.
[0118] Specifically, electronic devices can obtain prior knowledge by statistically determining the bit information of historical bit combinations. Then, electronic devices can determine the prior probability of the current bit combination using an Nth-order Markov process based on the prior knowledge of the current bit combination, the channel transition probability of the bit combination corresponding to the target decoding parameters in the previous frame, and the prior probability of the bit combination corresponding to the target decoding parameters in the previous frame.
[0119] Optionally, the prior knowledge can be 0th-order prior knowledge, 1st-order prior knowledge, or Nth-order prior knowledge.
[0120] It should be understood that the order of prior knowledge is the same as the order of a Markov process.
[0121] Optionally, when an electronic device determines prior probabilities through an Nth-order Markov process, the electronic device needs to store Nth-order prior knowledge. Nth-order prior knowledge requires 2... M(N+1) The storage space for each word is M, where M is the number of bits in the current bit combination. Furthermore, the larger N is, the more complex the process of calculating the prior probability becomes for the electronic device. Therefore, the value of N can be determined by the storage space of the electronic device, its performance, and the redundancy of the current bit combination. Additionally, a larger value of N results in better decoding performance for the electronic device.
[0122] For example, suppose the electronic device determines the prior probability using 0th-order prior knowledge (also known as AK0). This means the electronic device does not use the bit information of the bit combination corresponding to the target decoding parameters in the previous frame (or the previous N frames) of the current frame. Thus, the electronic device can process the 0th-order prior knowledge through a 0th-order Markov process to determine the prior probability of the current bit combination as follows:
[0123]
[0124] in, This represents the probability of the i-th bit combination that the data transmitting device may send for frame l (i.e., the current frame). This represents the 0th-order prior knowledge obtained by the electronic device through statistical analysis of historical frames corresponding to the current frame. Correspondingly, the posterior probability of the current bit combination determined by the 0th-order prior knowledge is:
[0125] If an electronic device determines the prior probability using first-order prior knowledge (also known as AK1), it means that the electronic device can use the bit information (i.e., first-order prior knowledge) of the bit combination corresponding to the target decoding parameters in the historical frame corresponding to the previous frame. Thus, the electronic device can also determine the prior probability of the current bit combination using first-order prior knowledge.
[0126]
[0127] in, This represents the probability that, in frame l-1 (i.e., the frame preceding the current frame), the bit combination corresponding to the target decoding parameters transmitted by the data transmitting device is the j-th bit combination, and the current bit combination of the current frame is the i-th bit combination. This refers to the first-order prior knowledge obtained by statistically analyzing the previous and current historical frames of an electronic device. This represents the channel transition probability of the current bit combination in the previous frame. This represents the prior probability of the bit combination corresponding to the current bit combination in the previous frame.
[0128] Accordingly, the electronic device determines the posterior probability of the current bit combination based on the prior probability corresponding to first-order prior knowledge as follows:
[0129]
[0130] Alternatively, the posterior probability of the current bit combination, determined by the prior probability corresponding to first-order prior knowledge, can also be:
[0131] Optionally, the posterior probability of the bit combination corresponding to the current bit combination in the previous frame (or the previous N frames) can also be referred to as prior knowledge.
[0132] For example, Figure 6 A schematic diagram illustrating decoding based on posterior probability is shown. The electronic device can determine the prior probability of the current bit combination using either 0th-order or 1st-order prior knowledge. Furthermore, the electronic device can determine the channel transition probability of the current bit combination using the log-likelihood ratio of each bit in the current bit combination. Then, the electronic device can determine the posterior probability of the current bit combination using the channel transition probability and the prior probability. Subsequently, the electronic device can determine the target decoding parameters corresponding to the current bit combination using the posterior probability.
[0133] Specifically, when determining the prior probability of the current bit combination in the current frame using first-order prior knowledge, the posterior probability of the current bit combination can be determined using the posterior probability of the bit combination corresponding to the current bit combination in the previous frame and the first-order prior knowledge.
[0134] In some embodiments, combined with Figure 5 ,like Figure 7 As shown, the current bit combination corresponds to multiple candidate bit combinations. The number of posterior probabilities for the current bit combination is also multiple. Each posterior probability corresponds to one candidate bit combination. In step S305 above, the electronic device determines the decoding result based on the posterior probability of the current bit combination, specifically including:
[0135] S701. The electronic device selects a posterior probability from multiple posterior probabilities that has a probability greater than a preset threshold, and determines the decoding parameters of the candidate bit combination corresponding to the posterior probability as the decoding result.
[0136] Candidate bit combinations refer to the bit combinations that the data transmitting device may send. The decoding result includes the target decoding parameters.
[0137] Optionally, the electronic device can select a posterior probability with a probability greater than a preset threshold, or it can select the posterior probability with the highest posterior probability. The decoding performance is best when the electronic device selects the posterior probability with the highest posterior probability.
[0138] Specifically, the electronic device can determine the target decoding parameters using the maximum a posteriori probability method: After determining multiple posterior probabilities, the electronic device determines the largest posterior probability (or the posterior probability with a probability greater than a preset threshold) as the target posterior probability. When the target posterior probability is large, it indicates that the data transmitting device is more likely to send the candidate bit combination corresponding to the target posterior probability. Therefore, the electronic device can determine the candidate bit combination corresponding to the target posterior probability as the actual bit combination to be sent. Then, the electronic device can determine the parameters corresponding to the actual bit combination as the target decoding parameters. When the target posterior probability is the maximum posterior probability, the specific formula is as follows:
[0139]
[0140] Among them, u (i) It is the quantization codebook entry of quantization index i, that is, the quantization codebook entry corresponding to the i-th bit combination sent by the data transmitting device, where i is the i-th bit combination that the data transmitting device may send.
[0141] It should be noted that electronic devices can determine the decoding parameters corresponding to multiple bit combinations that the data transmitting device may send by using a pre-stored quantization codebook.
[0142] For example, assume the posterior probabilities of the current bit combination are P(00|00) = 0.1, P(01|00) = 0.1, P(10|00) = 0.3, and P(11|00) = 0.5. Since P(11|00) has the highest posterior probability, the electronic device can determine that 11 is the actual bit combination sent by the data transmitting device. Subsequently, the electronic device can obtain the target decoding parameters corresponding to bit combination 11 obtained through the quantization codebook entry.
[0143] S702, The electronic device determines the decoding result by summing the products of the posterior probability of each candidate bit combination and the decoding parameters of each candidate bit combination.
[0144] Specifically, the electronic device can also determine the target decoding parameters using the least mean square error method: Since the data transmitting device may send multiple candidate bit combinations, and different candidate bit combinations correspond to different decoding parameters, the electronic device can determine multiple decoding parameters corresponding to multiple candidate bit combinations that the data transmitting device may send. Then, the electronic device can determine the target decoding parameter corresponding to the current bit combination by summing the products of the multiple decoding parameters and the posterior probability corresponding to each decoding parameter.
[0145] It should be noted that electronic devices can determine the decoding parameters corresponding to multiple bit combinations that the data transmitting device may send by using a pre-stored quantization codebook. Therefore, electronic devices can determine the target decoding parameters using the minimum mean square error method.
[0146]
[0147] Among them, u (i) It is the quantization codebook entry of quantization index i, where i is the i-th bit combination that the data transmitting device may send, and I is the I-th bit combination that the data transmitting device may send.
[0148] For example, the posterior probabilities of the current bit combinations are P(00|00) = 0.1, P(01|00) = 0.1, P(10|00) = 0.3, and P(11|00) = 0.5. The electronic device can determine, based on the quantization codebook, that the parameter corresponding to bit combination 00 sent by the data transmitting device is 1.0, the parameter corresponding to bit combination 01 is 1.1, the parameter corresponding to bit combination 10 is 0.9, and the parameter corresponding to bit combination 11 is 1.2. The electronic device can then determine the target decoding parameter using the minimum mean square error method: 0.1*1.0 + 0.1*1.1 + 0.3*0.9 + 0.5*1.2 = 1.1616. Therefore, the electronic device can determine the target decoding parameter as 1.1616.
[0149] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0150] This application embodiment can divide the decoding device into functional modules according to the above method example. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. Optionally, the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.
[0151] like Figure 8 The diagram shown is a structural schematic of a decoding device provided in an embodiment of this application. This decoding device can be used to perform... Figures 3-5 , Figure 7 The decoding method shown in any one of them. Figure 8 The decoding device shown includes: an acquisition unit 801 and a determination unit 802;
[0152] Acquisition unit 801 is used to acquire the current bit combination; the current bit combination includes at least one bit. For example, combined with Figure 3 The acquisition unit 801 is used to execute S301.
[0153] The determining unit 802 is used to determine the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination. For example, combined with Figure 3 Unit 802 is used to execute S302.
[0154] The determining unit 802 is further configured to determine the prior probability of the current bit combination based on the prior knowledge corresponding to the current bit combination; the prior knowledge includes bit information of received historical bit combinations. For example, combined with... Figure 3 Unit 802 is used to execute S303.
[0155] The determining unit 802 is also used to determine the posterior probability of the current bit combination based on the channel transition probability and the prior probability. For example, combined with Figure 3 Unit 802 is used to execute S304.
[0156] The determining unit 802 is also used to determine the decoding result based on the posterior probability of the current bit combination; the decoding result includes the target decoding parameters. For example, combined with Figure 3 Unit 802 is used to execute S305.
[0157] Optionally, the determining unit 802 is specifically used for:
[0158] The bit error rate of each bit in the current bit combination is determined based on the log-likelihood ratio of each bit in the current bit combination. For example, combining... Figure 4 Unit 802 is used to execute S401.
[0159] The channel transition probability of each bit in the current bit combination is determined based on the bit error rate of each bit in the current bit combination. For example, combined with... Figure 4 Unit 802 is used to execute S402.
[0160] The channel transition probability of the current bit combination is determined by multiplying the channel transition probabilities of multiple bits in the current bit combination. For example, combining... Figure 4 Unit 802 is used to execute S403.
[0161] Optionally, the determining unit 802 is specifically used for:
[0162] Prior knowledge is processed using an Nth-order Markov process to obtain the prior probability of the current bit combination. For example, combining... Figure 5 Unit 802 is used to execute S501.
[0163] Optionally, the current bit combination corresponds to multiple candidate bit combinations; the number of posterior probabilities for the current bit combination is multiple; one posterior probability corresponds to one candidate bit combination; the determining unit 802 is specifically used for:
[0164] From multiple posterior probabilities, a target posterior probability greater than a preset threshold is selected, and the decoding parameters of the candidate bit combination corresponding to the target posterior probability are determined as the decoding result. For example, combining... Figure 7 Unit 802 is used to execute S701.
[0165] The decoding result is determined by summing the products of the posterior probability of each candidate bit combination and the decoding parameters of each candidate bit combination. For example, combining... Figure 7 Unit 802 is used to execute S702.
[0166] This application also provides a computer-readable storage medium, which includes computer-executable instructions. When the computer-executable instructions are run on a computer, the computer performs the decoding method provided in the above embodiments.
[0167] This application also provides a computer program that can be directly loaded into a memory and contains software code. After being loaded and executed by a computer, the computer program can implement the decoding method provided in the above embodiments.
[0168] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this application can be implemented using hardware, software, firmware, or any combination thereof. When implemented in software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer-readable storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media can be any available medium accessible to a general-purpose or special-purpose computer.
[0169] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.
[0170] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and other division methods may exist in actual implementation. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate; components shown as units may be one physical unit or multiple physical units, i.e., they may be located in one place or distributed in multiple different places. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0171] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.
[0172] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A decoding method, characterized in that, include: Obtain the current bit combination; the current bit combination includes at least one bit; The channel transition probability of the current bit combination is determined based on the log-likelihood ratio of each bit in the current bit combination; The prior probability of the current bit combination is determined based on the prior knowledge corresponding to the current bit combination; the prior knowledge includes bit information of received historical bit combinations. The posterior probability of the current bit combination is determined based on the channel transition probability and the prior probability. The decoding result is determined based on the posterior probability of the current bit combination; the decoding result includes the target decoding parameters; Wherein, determining the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination includes: The bit error rate of each bit in the current bit combination is determined based on the log-likelihood ratio of each bit in the current bit combination; The channel transition probability of each bit in the current bit combination is determined based on the bit error rate of each bit in the current bit combination; The channel transition probability of the current bit combination is determined by multiplying the channel transition probabilities of multiple bits in the current bit combination.
2. The decoding method according to claim 1, characterized in that, Determining the prior probability of the current bit combination based on the prior knowledge corresponding to the current bit combination includes: based on N A Markov process is used to process the prior knowledge to obtain the prior probability of the current bit combination.
3. The decoding method according to claim 1 or 2, characterized in that, The current bit combination corresponds to multiple candidate bit combinations; the number of posterior probabilities of the current bit combination is multiple; one posterior probability corresponds to one candidate bit combination. Determining the decoding result based on the posterior probability of the current bit combination includes: A target posterior probability greater than a preset threshold is selected from multiple posterior probabilities, and the decoding parameters of the candidate bit combination corresponding to the target posterior probability are determined as the decoding result. Alternatively, the decoding result can be determined by summing the products of the posterior probability of each candidate bit combination and the decoding parameters of each candidate bit combination.
4. A decoding device, characterized in that, include: Acquiring and determining units; The acquisition unit is used to acquire the current bit combination; the current bit combination includes at least one bit; The determining unit is configured to determine the channel transition probability of the current bit combination based on the log-likelihood ratio of each bit in the current bit combination; The determining unit is further configured to determine the prior probability of the current bit combination based on the prior knowledge corresponding to the current bit combination; the prior knowledge includes bit information of received historical bit combinations; The determining unit is further configured to determine the posterior probability of the current bit combination based on the channel transition probability and the prior probability; The determining unit is further configured to determine the decoding result based on the posterior probability of the current bit combination; the decoding result includes target decoding parameters; The determining unit is specifically used for: The bit error rate of each bit in the current bit combination is determined based on the log-likelihood ratio of each bit in the current bit combination; The channel transition probability of each bit in the current bit combination is determined based on the bit error rate of each bit in the current bit combination; The channel transition probability of the current bit combination is determined by multiplying the channel transition probabilities of multiple bits in the current bit combination.
5. The decoding device according to claim 4, characterized in that, The determining unit is specifically used for: based on N A Markov process is used to process the prior knowledge to obtain the prior probability of the current bit combination.
6. The decoding device according to claim 4 or 5, characterized in that, The current bit combination corresponds to multiple candidate bit combinations; the number of posterior probabilities for the current bit combination is multiple; one posterior probability corresponds to one candidate bit combination; the determining unit is specifically used for: A target posterior probability greater than a preset threshold is selected from multiple posterior probabilities, and the decoding parameters of the candidate bit combination corresponding to the target posterior probability are determined as the decoding result. The decoding result is determined by summing the products of the posterior probability of each candidate bit combination and the decoding parameters of each candidate bit combination.
7. A decoding device, characterized in that, It includes a memory and a processor; the memory is used to store computer execution instructions, and the processor is connected to the memory via a bus; when the decoding device is running, the processor executes the computer execution instructions stored in the memory to cause the decoding device to perform the decoding method as described in any one of claims 1-3.
8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes computer-executable instructions that, when executed on a computer, cause the computer to perform the decoding method as described in any one of claims 1-3.