Turbo decoding method, decoder, equipment and storage medium

Abstract

The invention relates to the technical field of power line communication, and relates to a Turbo decoding method, a decoder, equipment and a storage medium. The Turbo decoding method comprises the following steps: obtaining observation information and iteration parameter information; during the first iteration, determining the state transition probability, the forward probability and the backward probability of the component encoder at each moment according to the observation information; from the second iteration to the last iteration, calculating the state transition probability, the forward probability and the backward probability of the component encoder at each moment according to the observation information and the output result of the last iteration; determining a decision log-likelihood ratio of the component encoder at each moment according to the state transition probability, the forward probability and the backward probability of the component encoder at each moment; and performing hard decision on the decision log-likelihood ratio output by the last iteration to obtain a decoding result. According to the invention, transmission of redundant information can be reduced, and the data processing amount of the decoder is reduced.

Description

Technical Field

[0001] The present invention relates to the field of power line communication technology, and in particular, to a Turbo decoding method, a decoder, a device, and a storage medium. Background Art

[0002] Turbo coding and decoding technology can adapt to complex channel environments due to its high error correction ability, and is widely used in power line communication (PLC) scenarios to ensure reliable long-distance transmission under low signal-to-noise ratio conditions. It is widely used in scenarios such as real-time control instruction transmission in smart grids (such as circuit breaker operations, fault isolation signals), remote upload of electricity meter data (power consumption, voltage / current monitoring), and power equipment status monitoring (such as transformer temperature, line fault detection).

[0003] The existing Turbo encoder is composed of two recursive systematic convolutional code (RSC) component encoders connected in parallel through an interleaver. During encoding, the original information sequence is directly input into the first component encoder, and at the same time, it is input into the second component encoder after being scrambled by the interleaver. Finally, the original sequence and the two parity sequences are multiplexed and output. The output encoded data is sent to the physical layer of the sending end through the data link layer of the sending end, and then sent to the power line through radio frequency. After passing through the power line, it reaches the receiving end. The physical layer of the receiving end decodes the signal received by radio frequency through a series of processes. The decoding process of the Turbo decoder adopts an iterative structure, and each component decoder performs soft input and soft output calculations based on a maximum a posteriori probability algorithm (such as Log-MAP): calculates the likelihood values of all possible state transitions at the current moment through the received parity sequence and the prior information (external information from another decoder).

[0004] The structure of the Turbo decoder corresponding to the existing Turbo decoding method is relatively complex, and different formulas need to be used to calculate the posterior probabilities at different times. Usually, additional multipliers and judgment logics need to be set to judge for time k; in addition, in the existing decoding method, in each iteration, the state transition probability, forward probability, and backward probability of the current iteration are usually calculated based on the state transition probability, forward probability, and backward probability output in the previous iteration, and the amount of data is very large; however, as the application scenarios of power line transmission become more and more complex, the requirement for the power line data transmission rate is also getting higher and higher. Therefore, it is necessary to reduce the delay of each module processed by the physical layer of the receiving end and simplify the hardware structure of the Turbo decoder. Summary of the Invention

[0005] This application aims to at least solve the technical problems existing in the prior art, and provides a Turbo decoding method, a system, a device, and a storage medium.

[0006] In a first aspect, a Turbo decoding method provided by the present invention includes:

[0007] S1. Obtain observation information and iterative parameter information. The observation information is the noisy observation value of the signal sequence encoded by the component encoder, and the iterative parameter information represents the maximum number of iterations of the decoder. Denote the maximum number of iterations as N, where N is a positive integer greater than 1;

[0008] S2. Initialize the current iteration number to 1;

[0009] S3. Determine whether the current iteration number is 1. If so, execute step S4; if not, execute step S5;

[0010] S4. Determine the state transition probability, forward probability, and backward probability of each moment of the component encoder according to the observation information;

[0011] S5. Obtain the extrinsic information and forward probability reference value output in the previous iteration, and determine the state transition probability, forward probability, and backward probability of each moment of the component encoder according to the observation information, extrinsic information, and forward probability reference value. The extrinsic information is used to represent the state transition probability estimation value of the component encoder at each moment;

[0012] S6. Determine the decision log-likelihood ratio of each moment of the component encoder according to the state transition probability, forward probability, and backward probability of each moment of the component encoder respectively;

[0013] S7. Determine whether the current iteration number is N. If so, execute step S8; if not, increment the iteration number by 1 and execute step S5;

[0014] S8. Perform a hard decision on the decision log-likelihood ratio to obtain the decoding result.

[0015] In a second aspect, the present invention provides a Turbo decoder, and the system includes:

[0016] At least two component decoders, which are used to cooperate to process the bit sequence in the observation information and output the state transition probability, forward probability, and backward probability of each moment of the component encoder;

[0017] A main control unit, which is used to control the component decoders according to the above Turbo decoding method;

[0018] An interleaver, which is used to restore the rearranged sequence output by the Turbo encoder to the original order;

[0019] An extrinsic information processing module, which is used to separate the extrinsic information from the output result of the current iteration of the component decoder, and the extrinsic information is used to calculate the state transition probability of the next iteration;

[0020] A decision module, configured to perform a hard decision on the decision log-likelihood ratio and output a decoding result.

[0021] In a third aspect, the present invention provides an electronic device, which includes:

[0022] At least one processor; and,

[0023] A memory communicatively connected to the at least one processor; wherein,

[0024] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the above-mentioned Turbo decoding method.

[0025] In a fourth aspect, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is executed by a processor in an electronic device to implement the above-mentioned Turbo decoding method.

[0026] In summary, the present application includes the following beneficial technical effects:

[0027] In the first iteration of the Turbo decoding method of the present application, the state transition probability, forward probability, and backward probability of each moment of the component encoder are determined based on the observation information; in the first iteration to the last iteration, according to the observation information, the external information output in the previous iteration, and the forward probability reference value, the state transition probability, forward probability, and backward probability of each moment of the component encoder are calculated; since the definition of the termination moment of the backward probability is the same as the definition of the starting moment of the forward probability, the present application only transfers the forward probability at the initial moment output in the current iteration to the next iteration, which can reduce the transfer of redundant information and reduce the data processing amount of the decoder;

[0028] After each iteration, the backward probability at the termination moment is initialized to 1, and the recurrence formula of the backward probability at non-termination moments is unified, eliminating a part of the multiplier and logic judgment module, thereby simplifying the hardware structure of the decoder. Description of the Drawings

[0029] Figure 1 It is a schematic flowchart of the Turbo decoding method provided by an embodiment of the present invention;

[0030] Figure 2 It is a program block diagram of an embodiment of the Turbo decoding method provided by an embodiment of the present invention;

[0031] Figure 3 It is a schematic structural diagram of an electronic device for implementing the Turbo decoding method provided by an embodiment of the present invention.

[0032] Reference numerals: 10, processor; 11, memory; 12, communication bus; 13, communication interface.

[0033] The realization, functional features and advantages of the objectives of the present invention will be further described in conjunction with the embodiments with reference to the accompanying drawings. Detailed implementation manners

[0034] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals indicate the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation to the present invention.

[0035] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention.

[0036] In the description of the present invention, unless otherwise specified and limited, it should be noted that the terms "installation", "connection" and "connection" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the communication inside two elements. It can be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific situations.

[0037] Refer to Figure 1 As shown, it is a schematic flow chart of a Turbo decoding method provided by an embodiment of the present invention. In this embodiment, a Turbo decoding method is applied to a power line communication scenario. The Turbo decoding includes:

[0038] S1. Obtain observation information and iterative parameter information.

[0039] The observation information is the noisy observation value of the signal sequence encoded by the component encoder. The observation information includes the noisy observation of the systematic bits and the noisy observation of the parity bits. The iterative parameter information represents the maximum number of iterations of the decoder. In this embodiment, the maximum number of iterations is denoted as N, and N is a positive integer greater than 1. The iterative parameter information can be set by the staff according to actual experience, and this application does not make any restrictions.

[0040] For the convenience of those skilled in the art, the processes of Turbo coding and Turbo decoding will be described below with specific examples.

[0041] Specifically, at the sending end, the Turbo component encoder is a discrete-time finite-state Markov process. Assume that the total number of time instants of the component encoder is K, k is the time instant index value, k ∈ [1, K]. At k = 0, the starting state of the Turbo component encoder is represented by s0; at k = 1,..., K - 1, the state of the Turbo component encoder is s k ∈ {000, 001, 010, 011, 100, 101, 110, 111} = {0, 1, 2, 3, 4, 5, 6, 7}; it should be noted that the state s of the Turbo component encoder at time instant k k and the parity bit c output by the Turbo component encoder at time instant k k , are only related to the systematic bit m input by the Turbo component encoder at time instant k k and the state s of the Turbo component encoder at time instant k - 1 k-1 .

[0042] In this embodiment, 2-bit information is input to the Turbo component encoder at each time instant, and the Turbo component encoder encrypts the input bit information to obtain the encrypted information where x k represents the encrypted information, this symbol means "defined as", and the encrypted information includes the systematic bit m at time instant k k and the parity bit c k ;

[0043] At the receiving end, the noisy observation of the output at time instant k by the sending end is where represents the noisy observation of the systematic bit m k , represents the noisy observation of the parity bit c k ; in the field of digital signal processing, the received data is usually referred to as the observation of the transmitted data. Since in the real world, signals are all transmitted in a noisy environment, the noisy observation is the observation information of the transmitted data by the receiving end in the presence of noise.

[0044] S2. Initialize the current iteration number to 1.

[0045] S3. Determine whether the current iteration number is 1. If so, execute step S4; if not, execute step S5.

[0046] S4. Calculate the state transition probability of each time instant of the component encoder according to the observation information.

[0047] S5. Obtain the external information and the forward probability reference value output in the previous iteration. According to the observation information, external information, and forward probability reference value, calculate the state transition probability, forward probability, and backward probability of the component encoder at each moment.

[0048] The external information is used to represent the estimated value of the state transition probability of the component encoder at each moment, and the external information is calculated using the decision log-likelihood ratio output in the previous iteration. Specifically, the generation steps of the external information include:

[0049] S51. Obtain the decision log-likelihood ratio at each moment in the previous iteration.

[0050] S52. Determine the corresponding external information at each moment in this iteration according to the decision log-likelihood ratio at each moment in the previous iteration. The external information is used to represent the estimated value of the state transition probability of the component encoder at each moment.

[0051] The external information output at the k-th moment in the n-th iteration The calculation formula is

[0052]

[0053] n is the index of the iteration times of the component decoder, n ∈ [2, N]; represents the decision log-likelihood ratio at the k-th moment, represents the channel log-likelihood ratio at the k-th moment, and the channel log-likelihood ratio at the k-th moment is obtained by demodulating the received noisy information; represents the external information output at the k-th moment in the (n - 1)-th iteration.

[0054] S6. Determine the decision log-likelihood ratio of the component encoder at each moment according to the state transition probability, forward probability, and backward probability of the component encoder at each moment respectively, and output the set of decision log-likelihood ratios of the component encoder.

[0055] S7. Determine whether the current iteration times is N. If so, execute step S8; otherwise, increment the iteration times by 1 and execute step S5.

[0056] S8. Perform a hard decision on the decision log-likelihood ratio to obtain the decoding result.

[0057] Determine whether the current iteration times reaches the maximum iteration times. If it reaches the maximum iteration times, perform a hard decision according to the decision log-likelihood ratio; otherwise, increment the iteration times by 1 and return to step S5 until the maximum iteration times is reached.

[0058] Refer to Figure 2 , and the calculation rules of the state transition probability, forward probability, and backward probability are explained in detail below:

[0059] In step S4, based on the noisy observation of the systematic bit m k and the noisy observation of the parity bit c k , calculate the state transition probabilities at K moments.

[0060] Define the state transition probability as γ k (m k , s k-1 , s k ), k = 1, …, K. The calculation formula for the state transition probability of the component encoder at moment k is:

[0061]

[0062] where γ k (m k , s k-1 , s k ) is the state transition probability at moment k, m k represents the systematic bit at moment k, s k-1 represents the state at moment k - 1, and s k represents the state at moment k; represents the noisy observation of the systematic bit, represents the noisy observation of the parity bit;

[0063] p(s k |s k-1 ) represents the probability that the state of the component encoder at moment k is s k-1 under the condition that the state of the component encoder at moment k - 1 is s k ; p(m k |s k-1 , s k ) represents the probability that the input of the component encoder at moment k is the systematic bit m k-1 under the condition that the state of the component encoder at moment k - 1 is s k and the state of the component encoder at moment k is s k . If this probability value exists for the state transition branch, it is 1; otherwise, it is 0.

[0064] represents the probability of obtaining the noisy observation of the systematic bit k under the condition that the input of the component encoder at moment k is m k-1 and the state of the component encoder at moment k - 1 is s k ; ; represents the probability that the input of the component encoder at moment k is m k and the state of the component encoder at moment k - 1 is s k-1and the state of the component encoder at time k is s k Under the condition, the noisy observation of the parity bit is obtained .

[0065] According to the state transition probability of the component encoder, through the recurrence formula of the forward probability, calculate the forward probability of the component encoder at all times k = 0, …, K in order from time 0 to time K:

[0066] Define the forward probability α k (s k ), k = 0, …, K:

[0067]

[0068] where p(s0) represents the probability that the starting state of the component encoder at time 0 is s0, represents the joint random variable (y1, …, y k ), represents that under the condition that the observed value is , the probability that the state of the component encoder at time k is s k .

[0069] In this embodiment, the calculation formula for the forward probability of the component encoder at time k is:

[0070]

[0071] α0(s0) represents the forward probability at the initial time, p(s0) represents the probability that the starting state of the component encoder at time 0 is s0. If the current iteration is the first iteration, then the value of p(s0) in the current iteration is taken as 1 / 8; if the current number of iterations is greater than 1, then the value of p(s0) in the current iteration is taken as the forward probability α K (s K ) at time K in the previous iteration; α k (s k ) represents the forward probability at time k, and α k-1 (s k-1 ) represents the forward probability at time k - 1.

[0072] Subsequently, according to the state transition probability and forward probability of the component encoder, determine the backward probability of the component encoder at each time, and calculate the backward probability at all times k = 1, …, K in order from time K to time 1 through the recurrence formula of the backward probability.

[0073] Define the backward probability β k (s k ), k = 1, …, K:

[0074]

[0075] where the backward probability β at time K K (s K ) is a constant value. At each iteration, the backward probability β at time K K (s K ) is initialized to 1. denotes the joint random variable (y1,…,y k ). denotes the joint random variable (y k+1 ,…,y K ). denotes the probability of obtaining the observation value under the condition that the observation value is . denotes the probability of obtaining the observation value k under the condition that the state of the component encoder at time k is s .

[0076] In this embodiment, the calculation formula for the backward probability of the component encoder at time k is:

[0077]

[0078]

[0079] where β k (s k ) represents the backward probability at time k, β k-1 (s k-1 ) represents the backward probability at time k - 1, γ k+1 (m k+1 , s k , s k+1 ) is the state transition probability at time k + 1, and β K (s K ) represents the backward probability at time K.

[0080] In the existing Turbo decoding method, the calculation methods for the backward probability at the boundary time and the backward probability at the non-boundary time are different. Therefore, the structure of the existing Turbo decoder usually needs to set additional multipliers and judgment logics to judge the time, and the structure of the Turbo decoder is relatively complex. By redefining the backward probability at the termination time k = K as β K (s K) = 1, such that the recursive calculation formula for the backward probability at the boundary time k = K - 1 is the same as that for the backward probability at non-boundary times k = 1, …, K - 2, eliminating the multiplier and the judgment logic. At the same time, since the value of the backward probability at the termination time k = K is fixed, the component decoder does not need to output this parameter for the next iteration, reducing the number of parameter outputs.

[0081] In the prior art solution, the definition of the backward probability at the termination time k = K is the same as the meaning of the forward probability at the starting time k = 0, so it does not bring additional extrinsic information to improve performance;

[0082] In this application, the backward probability at the key time output in this iteration is no longer passed to the next iteration. By reducing the transmission of redundant information and unifying the backward probability recursive structure, the hardware structure is simplified.

[0083] The following combines specific examples to explain the calculation process of determining the decision log-likelihood ratio at each time of the component encoder according to the state transition probability, forward probability, and backward probability at each time of the component encoder. Since in this embodiment, 2-bit information is input to the component encoder at each time, and each bit may take values of 0 or 1, there are four possible values for the bit information input to the component encoder: 00, 01, 10, or 11. When the bit information input to the component encoder is 00, the system bit m k corresponding value is 0; when the bit information input to the component encoder is 01, the system bit m k corresponding value is 1; when the bit information input to the component encoder is 10, the system bit m k corresponding value is 2; when the bit information input to the component encoder is 11, the system bit m k corresponding value is 3;

[0084] Therefore, when 2-bit information is input to the component encoder at each time, the calculation formula for the decision log-likelihood ratio is:

[0085]

[0086] Λ (1) (m k ) represents the first decision log-likelihood ratio, Λ (2) (m k ) represents the second decision log-likelihood ratio, Λ (3) (m k ) represents the third decision log-likelihood ratio, represents the probability that m input at time k of the component encoder is 1 (i.e., 01) under the condition that the observed value is k ; represents that under the condition that the observed value is Under the condition that, the probability that the input to the component encoder at time k is m k is 0 (i.e., 00); It represents that when the observed value is Under the condition that, the probability that the input to the component encoder at time k is m k is 2 (i.e., 10); It represents that when the observed value is Under the condition that, the probability that the input to the component encoder at time k is m k is 3 (i.e., 11).

[0087] When inputting 1-bit information to the component encoder at each moment, there are two possibilities for the bit information input to the component encoder, 0 or 1; therefore, when inputting 1-bit information to the component encoder at each moment, the calculation formula for the decision log-likelihood ratio is:

[0088]

[0089] Similarly, if 3-bit information is input to the component encoder at each moment, there are eight possibilities for the bit information input to the component encoder, 000, 001, 010, 011, 100, 101, 110, or 111. When inputting 3-bit information to the component encoder at each moment, 7 calculation formulas are required for the decision log-likelihood ratio. Those skilled in the art can determine the calculation formula for the decision log-likelihood ratio according to the number of bits of information input to the component encoder at each moment. For the sake of simplicity of the specification, this embodiment will not elaborate further.

[0090] In step S8, the rule for hard decision on the decision log-likelihood ratio is as follows:

[0091] When inputting 2-bit information to the component encoder at each moment, calculate the first decision log-likelihood ratio of Λ (1) (m k ), the second decision log-likelihood ratio Λ (2) (m k ), and the third decision log-likelihood ratio Λ (3) (m k ), and select the maximum value among Λ (1) (m k ), Λ (2) (m k ), Λ (3) (m k ) and. Denote the maximum value among Λ (1) (m k ), Λ (2) (m k ), Λ (3) (m k ) and as the target decision log-likelihood ratio value;

[0092] Compare the target decision log-likelihood ratio with a preset reference value. In this embodiment, the preset reference value is 0:

[0093] If the target decision log-likelihood ratio is less than the preset reference value, then the estimated value of system bit m k is

[0094] If the target decision log-likelihood ratio is greater than the preset reference value, and the target decision log-likelihood ratio is Λ (1) (m k ), then the estimated value of system bit m k is

[0095] If the target decision log-likelihood ratio is greater than the preset reference value, and the target decision log-likelihood ratio is Λ (2) (m k ), then the estimated value of system bit m k is

[0096] If the target decision log-likelihood ratio is greater than the preset reference value, and the target decision log-likelihood ratio is Λ (3) (m k ), then the estimated value of system bit m k is

[0097] Determine the decoding result according to the estimated value of system bit m k is .

[0098] Based on the same inventive concept, an embodiment of the present invention provides a Turbo decoder.

[0099] The Turbo decoder includes at least two component decoders, a main control unit, an interleaver, an external information processing module, and a decision module that are communicatively connected to each other.

[0100] The two component decoders can cooperate to process the bit sequence in the observation information and output the state transition probability, forward probability, and backward probability of each component encoder at each moment;

[0101] The main control unit can control the component decoders based on the above Turbo decoding method;

[0102] The interleaver of the Turbo encoder rearranges the bit sequence corresponding to the observation information to obtain a rearranged sequence; the deinterleaver can restore the rearranged sequence output by the Turbo encoder to the original order;

[0103] The external information processing module can separate the external information from the output result of the current iteration of the component decoder, and the external information is used to calculate the state transition probability of the next iteration;

[0104] The decision module can perform a hard decision on the decision log-likelihood ratio and output the decoding result.

[0105] The various change methods and specific examples in the Turbo decoding method provided in the above embodiments are equally applicable to the Turbo decoder of this embodiment. Through the foregoing detailed description of the Turbo decoding method, those skilled in the art can clearly know the implementation method of the Turbo decoder in this embodiment. For the sake of brevity of the specification, it will not be elaborated here.

[0106] This application also discloses an electronic device, as Figure 3 shown, which is a schematic structural diagram of an electronic device for the Turbo decoding method provided in an embodiment of the present invention. The electronic device may include at least one processor 10, a memory 11 communicatively connected to the at least one processor, a communication bus 12, and a communication interface 13. It may also include a computer program stored in the memory 11 and executable on the processor 10, such as a Turbo decoding method program.

[0107] Among them, the processor 10 may be composed of integrated circuits in some embodiments. For example, it may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits with the same or different functions, including a combination of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control core (Control Unit) of the electronic device, connecting various components of the entire electronic device through various interfaces and lines, and by running or executing programs or modules stored in the memory 11 (such as executing the Turbo decoding method, etc.), and calling data stored in the memory 11, to perform various functions of the electronic device and process data.

[0108] The memory 11 includes at least one type of readable storage medium, which includes flash memory, mobile hard disks, multimedia cards, card-type memories (such as SD or DX memories, etc.), magnetic memories, magnetic disks, optical discs, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device, such as the mobile hard disk of the electronic device. In some other embodiments, the memory 11 can also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the electronic device. Further, the memory 11 can also include both the internal storage unit and the external storage device of the electronic device. The memory 11 can be used not only to store application software installed in the electronic device and various types of data, such as the code of the Turbo decoding method program, etc., but also to temporarily store data that has been output or will be output.

[0109] The communication bus 12 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection and communication between the memory 11 and at least one processor 10, etc.

[0110] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface can include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), and is generally used to establish a communication connection between this electronic device and other electronic devices. The user interface can be a display, an input unit (such as a keyboard), and optionally, the user interface can also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. Among them, the display can also be appropriately referred to as a display screen or a display unit, and is used to display the information processed in the electronic device and to display a visual user interface.

[0111] Figure 3 Only the electronic device with components is shown. Those skilled in the art can understand that Figure 3The structures shown do not constitute a limitation on the electronic device, and it may include fewer or more components than those shown, or combine certain components, or have different component arrangements. For example, although not shown, the electronic device may further include a power source (such as a battery) for powering each component. Preferably, the power source can be logically connected to at least one processor 10 through a power management device, so as to implement functions such as charging management, discharging management, and power consumption management through the power management device. The power source may also include any components such as one or more DC or AC power sources, a recharge device, a power failure detection circuit, a power converter or inverter, and a power status indicator. The electronic device may also include various sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be elaborated here.

[0112] It should be understood that the embodiments are for illustrative purposes only and are not limited by this structure in the scope of the patent application.

[0113] Furthermore, if the modules / units integrated in the electronic device are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile.

[0114] The embodiments of the present application provide a computer-readable storage medium, for example, including: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory). The computer-readable storage medium stores a computer program that can be loaded and executed by a processor to perform the Turbo decoding method in the above embodiments.

[0115] In the description of this specification, the descriptions with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", "one implementation manner", "one preferred implementation manner", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0116] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and purposes of the present invention. The scope of the present invention is defined by the claims and their equivalents.

Claims

1. A Turbo decoding method, characterized in that: The method comprises: S1. Obtain observation information and iteration parameter information, where the observation information is a noisy observation value of a signal sequence encoded by a component encoder, and the iteration parameter information indicates a maximum number of iterations of a decoder, where the maximum number of iterations is denoted by N, where N is a positive integer greater than 1; S2, initialize the current number of iterations to 1; S3, determine whether the current number of iterations is 1, if so, execute step S4, if not, execute step S5; S4, determining the state transition probability, forward probability and backward probability of the component encoder at each moment according to the observation information; S5, obtaining the external information and forward probability reference value outputted in the previous iteration, and determining the state transition probability, forward probability and backward probability of the component encoder at each moment according to the observed information, the external information and the forward probability reference value, wherein the external information is used to represent the estimated value of the state transition probability of the component encoder at each moment; S6, determining the decision log-likelihood ratio of the component encoder at each moment according to the state transition probability, forward probability and backward probability of the component encoder at each moment; S7, determine whether the current number of iterations is N, if so, execute step S8, if not, increase the number of iterations by 1, and execute step S5; S8. Perform a hard decision on the decision log-likelihood ratio to obtain a decoding result.

2. The Turbo decoding method according to claim 1, wherein: The observation information includes the system bit noisy observation and the check bit noisy observation. The calculation formula of the state transition probability of the component encoder at time k is: Among them, γ k (m k ,s k-1 ,s k ) is the state transition probability at time k, k = 1, ..., K, K is the total number of time points, k is the time index value, m k represents the system bit at time k, s k-1 represents the state at time k-1, s k represents the state at time k; represents the system bit noisy observation, indicates that the check bit is noisy observation; p(s k |s k-1 ) indicates that the state of the component encoder at time k-1 is s k-1 Under the condition of k The probability of p(m k |s k-1 ,s k ) indicates that the state of the component encoder at time k-1 is s k-1 And the state of the component encoder at time k is s k Under the condition of k probability; Indicates that the input of the component encoder at time k is m k And the state of the component encoder at time k-1 is s k-1 And the state of the component encoder at time k is s k Under the condition of probability; Indicates that the input of the component encoder at time k is m k And the state of the component encoder at time k-1 is s k-1 And the state of the component encoder at time k is s k Under the condition of probability.

3. The Turbo decoding method according to claim 2, wherein: The calculation formula of the forward probability of the component encoder at time k is: α0s0 represents the forward probability at the initial time, p(s0) represents the probability that the initial state of the component encoder at time 0 is s0, α k (s k ) represents the forward probability at time k, α k-1 (s k-1 ) represents the forward probability at time k-1.

4. The Turbo decoding method according to claim 3, wherein: If the current iteration is the first iteration, the value of p(s0) in the current iteration is set to 1 / 8; If the current iteration number is greater than 1, the value of p(s0) in the current iteration is taken as the forward probability α at time K in the previous iteration. K (s K ).

5. The Turbo decoding method according to claim 3, wherein: The calculation formula of the backward probability of the component encoder at time k is: Among them, β k (s k ) represents the backward probability at time k, β k-1 (s k-1 ) represents the backward probability at time k-1, γ k+1 (m k+1 ,s k ,s k+1 ) is the state transition probability at time k+1, β k (s K ) represents the backward probability at time K.

6. The Turbo decoding method according to claim 1, wherein: The steps of generating external information include: Obtain the decision log-likelihood ratio at each moment in the previous iteration; The external information corresponding to each moment of this iteration is determined according to the decision log-likelihood ratio at each moment in the previous iteration.

7. The Turbo decoding method according to claim 6, wherein: External information output at time k in the nth iteration The calculation formula is n is the index of the number of component decoder iterations, n∈[2,N]; represents the decision log-likelihood ratio at time k, represents the channel log-likelihood ratio at time k, Represents the external information output at time k in the n-1th iteration.

8. A turbo decoder, used to implement the turbo decoding method according to any one of claims 1 to 7, characterized in that: include: At least two component decoders, used to cooperate in processing the bit sequence in the observation information and output the state transition probability, forward probability and backward probability of the component encoder at each moment; A main control unit, configured to control a component decoder based on the Turbo decoding method according to any one of claims 1 to 7; A deinterleaver, used to restore the rearranged sequence output by the Turbo encoder to its original order; An external information processing module, used to separate external information from the output results of the component decoder in this iteration, and the external information is used to calculate the state transition probability of the next iteration; The decision module is used to make a hard decision on the decision log-likelihood ratio and output a decoding result.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor (10); and, a memory (11) communicatively connected to the at least one processor (10); The memory (11) stores a computer program executable by the at least one processor (10), and the computer program is executed by the at least one processor (10) so that the at least one processor (10) can execute the Turbo decoding method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program; when the computer program is executed by a processor, the Turbo decoding method according to any one of claims 1 to 7 is implemented.

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