Soft information calculation method, device, electronic device and storage medium

Abstract

The present disclosure provides a method, apparatus, electronic device, and storage medium for calculating soft information, including: obtaining a received signal and a constellation diagram of a communication system under a target modulation mode; determining a first boundary value and a second boundary value of the modulation mode based on the received signal and the constellation diagram; and calculating first soft information and second soft information of the communication system under the target modulation mode based on the first boundary value and the second boundary value. In the present disclosure, the received signal and the constellation diagram of the current modulation mode are first determined, and then the first boundary value and the second boundary value of the modulation mode are determined based on the received signal and the constellation diagram. Finally, the first soft information and the second soft information are calculated based on the first boundary value and the second boundary value.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless digital transmission, and in particular to a soft information calculation method, device, electronic equipment and storage medium. Background Art

[0002] With the development of modern wireless communication systems, 4G technology has matured, and 5G is gaining widespread adoption and application. These communication technologies are all based on improving the spectrum efficiency of communication systems. OFDM is a communication system that effectively improves system spectrum efficiency. The mQAM modulation scheme it uses can significantly improve system spectrum efficiency. However, high-order modulation schemes can increase the system bit error rate (BER) during demodulation. To reduce the BER, the conventional hard decision method can be converted to a soft decision method that utilizes soft information for decision making, significantly improving the system's BER performance.

[0003] Conventional soft decision simplification methods typically use Gray-mapping constellations to calculate Euclidean distances, or employ block-wise calculations on the complex plane. These methods require calculating the Euclidean distances between points on the constellation, resulting in relatively high computational complexity. Furthermore, due to this computational complexity, the computational effort increases exponentially with higher modulation orders, making these methods inapplicable to higher-order modulations. Consequently, they are unable to meet the requirements of some ultra-high-order encryption systems. Summary of the Invention

[0004] In view of this, the purpose of the present disclosure is to provide a method, device, electronic device and storage medium for calculating soft information.

[0005] As one aspect of the present disclosure, a method for calculating soft information is provided, characterized by comprising:

[0006] Obtain the received signal and constellation diagram of the communication system under the target modulation mode;

[0007] Determine a first boundary value and a second boundary value of the modulation mode according to the received signal and the constellation diagram;

[0008] The first soft information and the second soft information of the communication system under the target modulation mode are calculated based on the first boundary value and the second boundary value.

[0009] Optionally, determining the first boundary value and the second boundary value of the modulation mode according to the received signal and the constellation diagram includes:

[0010] determining a first signal path and a second signal path of the received signal;

[0011] Mapping the first signal path and the second signal path on the constellation diagram to obtain mapped first signal path and second signal path;

[0012] establishing a coordinate system based on the mapped first signal path and the second signal path;

[0013] The first boundary value and the second boundary value are determined according to the coordinate system.

[0014] Optionally, determining the first boundary value and the second boundary value according to the coordinate system includes:

[0015] Determining a plurality of first constellation points on the mapped first signal path on a horizontal axis in the coordinate system, and taking an intermediate value between every two adjacent constellation points among the plurality of first constellation points as a first boundary value;

[0016] A plurality of second constellation points on the mapped second signal path are determined on the vertical axis in the coordinate system, and an intermediate value between every two adjacent constellation points among the plurality of second constellation points is used as a second boundary value.

[0017] Optionally, the calculating, based on the first boundary value, first soft information of the communication system under the target modulation mode includes:

[0018] quantizing the first boundary value to obtain a quantized first boundary value;

[0019] Determine a first mapping point in the first boundary value after the quantization process whose distance from the received signal is a first preset value and a second mapping point whose distance from the received signal is a second preset value;

[0020] Performing a difference calculation on the first mapping point and the second mapping point to obtain first soft information;

[0021] The first soft information is expressed as:

[0022] LLR1=|d1(r Ii )-d0(r Ii )|

[0023] Among them, LLR1 represents the first soft information, d0(r Ii ) represents the first mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 0, d1(r Ii ) represents the second mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 1.

[0024] Optionally, the first boundary value is quantized to obtain the quantized first boundary value, which is expressed as:

[0025]

[0026] Among them, t i represents the first boundary value, d0(r Ii ) represents the first mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 0, d1(r Ii ) represents the distance of the second mapping point, i.e. the constellation diagram with the closest mapping point to the received signal being 1, where r Ii represents the i-th bit received value of the data on the first signal path after mapping under the current modulation format, and a is the unit amplitude of the modulation constellation diagram.

[0027] Optionally, the calculating, based on the second boundary value, second soft information of the communication system under the target modulation mode includes:

[0028] quantizing the second boundary value to obtain a quantized second boundary value;

[0029] Determine a third mapping point whose distance from the received signal is a third preset value and a fourth mapping point whose distance from the received signal is a fourth preset value in the second boundary value after the quantization process;

[0030] performing a difference calculation on the third mapping point and the fourth mapping point to obtain second soft information;

[0031] The second soft information is expressed as:

[0032] LLR2=|d1(r Qi )-d0(r Qi )|

[0033] Among them, LLR2 represents the second soft information, d0(r Qi ) represents the third mapping point, which is the distance from the constellation diagram with the closest mapping point to the received signal being 0, d1(r Qi ) represents the fourth mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 1.

[0034] Optionally, the second boundary value is quantized to obtain a quantized second boundary value, which is expressed as:

[0035]

[0036] Among them, t j represents the second boundary value, d0(r Qi ) represents the third mapping point, which is the distance from the constellation diagram with the closest mapping point to the received signal being 0, d1(r Qi) represents the fourth mapping point, i.e. the distance from the constellation diagram of the mapping point closest to the received signal is 1, where r Qi represents the i-th bit received value of the data on the second signal path after mapping under the current modulation format, and a is the unit amplitude of the modulation constellation diagram.

[0037] As a second aspect of the present disclosure, the present disclosure further provides a soft information computing device, comprising:

[0038] The signal acquisition module is configured to: acquire a received signal and a constellation diagram of the communication system under a target modulation mode;

[0039] A boundary value calculation module is configured to: determine a first boundary value and a second boundary value of the modulation mode according to the received signal and the constellation diagram;

[0040] The soft information calculation module is configured to calculate the first soft information and the second soft information of the communication system under the target modulation mode based on the first boundary value and the second boundary value.

[0041] As a third aspect of the present disclosure, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the program, the calculation method of the soft information provided in the present disclosure is implemented.

[0042] As a fourth aspect of the present disclosure, the present disclosure further provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute any of the methods described above.

[0043] As described above, the present disclosure provides a method, apparatus, electronic device, and storage medium for calculating soft information. In the present disclosure, a received signal and a constellation diagram for a current modulation scheme are first determined. A first boundary value and a second boundary value for this modulation scheme are then determined using the received signal and the constellation diagram. Finally, first and second soft information are calculated using the first and second boundary values. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1A A schematic diagram of a method for calculating soft information provided by an embodiment of the present disclosure.

[0046] Figure 1B A schematic diagram of a method for calculating first soft information provided by an embodiment of the present disclosure.

[0047] Figure 1C A schematic diagram of a method for calculating second soft information provided by an embodiment of the present disclosure.

[0048] Figure 2 A schematic diagram of the structure of a soft information computing device provided in an embodiment of the present disclosure.

[0049] Figure 3 A schematic diagram of the electronic device structure of a method for calculating soft information provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0050] In order to make the objectives, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0051] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should have the usual meanings understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the embodiments of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the described object changes, the relative position relationship may also change accordingly.

[0052] In current communication system research, when it is necessary to reduce the bit error rate of a communication system, the general hard decision method can be converted into a soft decision method that uses soft information to make decisions, which can significantly improve the bit error rate performance of the communication system.

[0053] Research has shown that in additive white Gaussian noise (AWGN) channels, soft decisions achieve a 2dB soft decision gain over hard decisions, and in fading channels, the soft decision gain exceeds 3dB. However, for high-order mQAM, although the I and Q signals are independently mapped, each modulation symbol corresponds to multiple bits, and soft decisions must be calculated for each bit. Therefore, the soft information calculation process for high-order modulation is relatively complex. Programmable FPGAs, with their high integration, fast processing speed, and high execution efficiency, are widely used in the communications field. The decoder on the decoding side requires soft information from the received signal for accurate decoding. Therefore, the method used to calculate soft information significantly impacts the overall performance of the communication system.

[0054] Conventional soft-decision simplification methods typically require calculating Euclidean distances using a Gray-mapping constellation diagram, or employing complex-plane block-wise calculations. Consequently, these traditional methods require calculating the Euclidean distances between points on the constellation diagram, resulting in relatively high computational complexity. Furthermore, this computational complexity increases exponentially with higher modulation orders, making it difficult to directly apply these methods to higher-order modulations and, consequently, unable to meet the requirements of ultra-high-order encryption systems.

[0055] To address the above-mentioned issues, the present disclosure provides a method, apparatus, electronic device, and storage medium for calculating soft information. Using the above-mentioned method, the present disclosure first determines the received signal and constellation diagram of the current modulation scheme. Then, based on the received signal and constellation diagram, a first boundary value and a second boundary value for the modulation scheme are determined. Finally, the first and second soft information are calculated based on the first and second boundary values.

[0056] After introducing the basic principles of the present disclosure, various non-limiting embodiments of the present disclosure are described in detail below.

[0057] Figure 1A A schematic diagram of a method for calculating soft information provided by an embodiment of the present disclosure.

[0058] Figure 1A The calculation method of the soft information shown further comprises the following steps:

[0059] Step S10: Acquire a received signal and a constellation diagram of the communication system under a target modulation mode.

[0060] In some optional embodiments, when the bit error rate of the communication system needs to be reduced, the general hard decision method can be converted into a soft decision method that uses soft information to make decisions, which can significantly improve the bit error rate performance of the communication system.

[0061] In some optional embodiments, soft decision making can be accomplished by calculating soft information. In the initial stage of calculating the soft information, the modulation scheme used by the communication system (e.g., mQAM modulation) can be determined, and then the constellation diagram of the corresponding modulation scheme and the received signal can be obtained. Generally speaking, for mQAM, the number of bits it can contain should be log2m, with the mapped bits denoted as a and the received signal denoted as r. The soft information can then be calculated based on the obtained received signal and constellation diagram.

[0062] In some optional embodiments, using the 16QAM constellation as an example, the 16QAM modulated signal can consist of 2 bits of data each on the I and Q channels, comprising a 2-bit in-phase component and a 2-bit quadrature component, respectively. Because the I and Q signals are orthogonal to each other, the influence of the ordinate can be ignored when calculating the LLR (soft information) of the I-channel mapped symbols, and the influence of the abscissa can be ignored when calculating the LLR of the Q-channel mapped symbols. Furthermore, due to the symmetry of the I and Q signals, this characteristic allows the LLRs of the I and Q signals to be calculated separately.

[0063] Step S20: Determine a first boundary value and a second boundary value of the modulation mode according to the received signal and the constellation diagram.

[0064] In some optional embodiments, step S20 further specifically includes:

[0065] S201: Determine a first signal path and a second signal path of the received signal.

[0066] S202: Map the first signal path and the second signal path on the constellation diagram to obtain mapped first signal path and second signal path.

[0067] S203: Establishing a coordinate system based on the mapped first signal path and the second signal path.

[0068] S204: Determine the first boundary value and the second boundary value according to the coordinate system.

[0069] In some optional embodiments, after the modulation scheme of the received signal is determined, the signal paths of the received signal (i.e., the first signal path I and the second signal path Q) may also be determined. The determined signal paths may then be mapped onto the constellation diagram of the modulation scheme obtained in the above steps to obtain the mapped first signal path and second signal path.

[0070] In some optional embodiments, after obtaining the mapped first signal path and the second signal path, a one-dimensional rectangular coordinate system can be constructed. It is understandable that since the dimension of the constructed rectangular coordinate system is one-dimensional, this can make the subsequent calculation process more convenient.

[0071] In some optional embodiments, after the coordinate system is constructed, several boundary points under this modulation mode can be determined by the positions of each constellation point in the coordinate system, and then the calculation of soft information can be completed through the several boundary points.

[0072] In some optional embodiments, step S204 further specifically includes:

[0073] S2041: Determine a plurality of first constellation points on the mapped first signal path on the horizontal axis of the coordinate system, and use an intermediate value between every two adjacent constellation points among the plurality of first constellation points as a first boundary value.

[0074] S2042: Determine a plurality of second constellation points on the mapped second signal path on the vertical axis in the coordinate system, and use the middle value between every two adjacent constellation points among the plurality of second constellation points as a second boundary value.

[0075] In some optional embodiments, based on signal symmetry and orthogonal independence, the boundary value of path I (the first signal path) can be calculated first. When calculating, the boundary value can be reasonably divided according to the current signal landing point. For any mQAM, the boundary value should be The reasonable range of the current bit distance operation can be divided by the boundary value, which is the midpoint value of the two nearest constellation points with the same bit value for the i-th bit on the i-th path on the constellation diagram.

[0076] In some optional embodiments, after calculating the boundary value of the I path (first signal path), the boundary value of the Q path (second signal path) can be calculated by the same method. Specifically, the boundary value can also be reasonably divided according to the current signal landing point. For any mQAM, the boundary value should be The boundary value can be used to divide the reasonable range of the current bit distance operation. The boundary value is the midpoint value of the two nearest constellation points with the same bit value for the i-th bit on the Q path on the constellation diagram.

[0077] Step S30: Calculating first soft information and second soft information of the communication system under the target modulation mode based on the first boundary value and the second boundary value.

[0078] Figure 1B A schematic diagram of a method for calculating first soft information provided by an embodiment of the present disclosure.

[0079] In some optional embodiments, such as Figure 1B Step S30 shown specifically includes:

[0080] S301: quantize the first boundary value to obtain the quantized first boundary value.

[0081] S302: Determine a first mapping point in the first boundary value after the quantization process, the first mapping point of which is at a first preset distance from the received signal, and a second mapping point of which is at a second preset distance from the received signal.

[0082] S303: Perform difference calculation on the first mapping point and the second mapping point to obtain first soft information.

[0083] In some optional embodiments, after obtaining a plurality of first boundary values ​​and a plurality of second boundary values, the first soft information and the second soft information may be obtained by performing calculations based on the plurality of first boundary values ​​and the plurality of second boundary values.

[0084] In some optional embodiments, the first soft information can be calculated using a first boundary value. Specifically, the first boundary value can be quantized to convert the first boundary values ​​into a finite number of discrete values. A first mapping point with a first preset distance from the received signal and a second mapping point with a second preset distance from the received signal can then be determined within the quantized first boundary value. It will be appreciated that the first and second preset values ​​are pre-assumed values ​​and can be arbitrary numbers.

[0085] In some optional embodiments, the first boundary value is quantized to obtain the quantized first boundary value, which can be expressed as:

[0086]

[0087] Among them, t i represents the first boundary value, d0(r Ii ) represents the first mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 0, d1(r Ii ) represents the distance of the second mapping point, i.e. the constellation diagram with the closest mapping point to the received signal being 1, where r Ii represents the i-th bit received value of the data on the first signal path after mapping under the current modulation format, and a is the unit amplitude of the modulation constellation diagram.

[0088] In some optional embodiments, after obtaining the first mapping point and the second mapping point, a difference calculation may be performed between the two, and the absolute value of the result of the difference calculation is used as the final calculation result of the first soft information.

[0089] In some optional embodiments, the process of performing difference calculation on the first mapping point and the second mapping point to obtain the first soft information can be expressed as:

[0090] LLR1=|d1(r Ii )-d0(r Ii )|

[0091] Among them, LLR1 represents the first soft information, d0(r Ii ) represents the first mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 0, d1(r Ii ) represents the second mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 1.

[0092] Figure 1C A schematic diagram of a method for calculating second soft information provided by an embodiment of the present disclosure.

[0093] In some optional embodiments, such as Figure 1C The step S30 further specifically includes:

[0094] S304: quantize the second boundary value to obtain a quantized second boundary value.

[0095] S305: Determine a third mapping point in the second boundary value after the quantization process, the third mapping point of which is at a third preset distance from the received signal, and a fourth mapping point of which is at a fourth preset distance from the received signal.

[0096] S306: Perform difference calculation on the third mapping point and the fourth mapping point to obtain second soft information.

[0097] In some optional embodiments, after obtaining the first soft information, the second soft information can also be calculated using the above method. Specifically, the second boundary values ​​can be first quantized to convert the plurality of second boundary values ​​into a finite number of discrete values. A third mapping point with a third preset distance from the aforementioned received signal and a fourth mapping point with a fourth preset distance from the received signal can then be determined within the quantized second boundary values. It will be appreciated that the third and fourth preset values ​​are pre-assumed values ​​and can be arbitrary numbers.

[0098] In some optional embodiments, the second boundary value is quantized to obtain the quantized second boundary value, which can be expressed as:

[0099]

[0100] Among them, t j represents the second boundary value, d0(rQi ) represents the third mapping point, which is the distance from the constellation diagram with the closest mapping point to the received signal being 0, d1(r Qi ) represents the fourth mapping point, i.e. the distance from the constellation diagram of the mapping point closest to the received signal is 1, where r Qi represents the i-th bit received value of the data on the second signal path after mapping under the current modulation format, and a is the unit amplitude of the modulation constellation diagram.

[0101] In some optional embodiments, after obtaining the third mapping point and the fourth mapping point, a difference calculation may be performed between the two, and the absolute value of the result of the difference calculation is used as the final calculation result of the second soft information.

[0102] In some optional embodiments, the process of performing difference calculation on the third mapping point and the fourth mapping point to obtain the second soft information can be expressed as:

[0103] LLR2=|d1(r Qi )-d0(r Qi )|

[0104] Among them, LLR2 represents the second soft information, d0(r Qi ) represents the third mapping point, which is the distance from the constellation diagram with the closest mapping point to the received signal being 0, d1(r Qi ) represents the fourth mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 1.

[0105] In summary, the present disclosure determines the first and second boundary values ​​using the constellation diagram of the current modulation scheme and the received signal. Soft information (the first log-likelihood ratio and the second log-likelihood ratio) is then calculated using the first and second boundary values. This ultimately simplifies the calculation of soft information and enables its application in a wider range of scenarios.

[0106] In addition to providing the aforementioned soft information calculation method, this disclosure also optimizes the relevant characteristics of the hardware module and the reception buffer and downstream output of soft information. Specifically, to ensure the real-time communication of the communication system, the current operation can be pipelined to ensure efficient operation.

[0107] At the same time, because the computing module optimized by this disclosure focuses on matching multiple new encoding methods and integrates the relevant input, output and control signals of the relevant protocol interfaces, it maximizes the performance of this module while also maximizing its versatility. The optimization process of this hardware module can be expressed as:

[0108] In some optional embodiments, first, data preparation can be received first. Specifically, according to the standard bus protocol (AXI-Stream), when the preparation signal of this module is high, the upstream receiving end module starts to output data. Then, a first-in-first-out queue (FIFO) state judgment can be performed, specifically including that the received data will first be placed in the FIFO for buffering, and when the received data is a whole code word information and the calculation module is ready to calculate, the current whole code word information is output. Afterwards, a calculation module state judgment can be performed, specifically including that the calculation module calculates with each complete code word as a unit, and when the current operation is completed and enters the idle state, the FIFO inputs the next complete code word into the current module for calculation.

[0109] In some optional embodiments, format conversion can then be performed, specifically including converting the current data to an appropriate format based on the relevant information of the current coding block. That is, after receiving an entire codeword, subsequent calculation processes are performed to ensure the accuracy of the current codeword calculation. At the same time, the codeword is processed in blocks and in parallel, multiple computing modules are reused to improve computing efficiency. Then, fast calculation can be performed, specifically including fast calculation of soft information according to the above-mentioned soft information calculation method, and the calculation results are synchronously input to the output matching end for pipeline processing.

[0110] In some optional embodiments, output matching can be performed afterwards, specifically including, according to the input settings of the downstream decoder, reasonably allocating the number of single-cycle outputs and quantization accuracy of the current soft information. This configuration is consistent with the encoder configuration. For example, for polar code encoding and decoding under the 5G standard, 8-bit quantization accuracy can be used to describe each soft information to achieve decoding accuracy and efficiency. Then, for the current codeword, the correct decoding output size should be eight times the codeword bit. Finally, the decoder status can be judged, specifically including, according to the standard AXI-Stream protocol, when the ready signal of the downstream decoder is high, the data of the current module starts to be output, and the valid signal is high, thereby matching the output form of the standard AXI-Stream protocol.

[0111] Based on the same technical concept, corresponding to any of the above embodiments and methods, the present disclosure further provides a soft information calculation device. The soft information calculation method described in any of the above embodiments can be implemented through the soft information calculation device provided by the present disclosure.

[0112] Figure 2 A schematic diagram of the structure of a soft information computing device provided in an embodiment of the present disclosure.

[0113] Figure 2 The soft information calculation device shown further includes the following modules:

[0114] Signal acquisition module 10, boundary value calculation module 20 and soft information calculation module 30;

[0115] The signal acquisition module 10 is configured to acquire a received signal and a constellation diagram of the communication system under a target modulation mode.

[0116] The boundary value calculation module 20 is configured to determine the first boundary value and the second boundary value of the modulation mode according to the received signal and the constellation diagram. Specifically, the following steps are performed:

[0117] determining a first signal path and a second signal path of the received signal;

[0118] Mapping the first signal path and the second signal path on the constellation diagram to obtain mapped first signal path and second signal path;

[0119] establishing a coordinate system based on the mapped first signal path and the second signal path;

[0120] determining the first boundary value and the second boundary value according to the coordinate system;

[0121] Determining a plurality of first constellation points on the mapped first signal path on a horizontal axis in the coordinate system, and taking an intermediate value between every two adjacent constellation points among the plurality of first constellation points as a first boundary value;

[0122] A plurality of second constellation points on the mapped second signal path are determined on the vertical axis in the coordinate system, and an intermediate value between every two adjacent constellation points among the plurality of second constellation points is used as a second boundary value.

[0123] The soft information calculation module 30 is configured to calculate the first soft information and the second soft information of the communication system under the target modulation mode based on the first boundary value and the second boundary value. Specifically, the following steps are performed:

[0124] quantizing the first boundary value to obtain a quantized first boundary value;

[0125] Determine a first mapping point whose distance from the received signal is a first preset value and a second mapping point whose distance from the received signal is a second preset value in the first boundary value after the quantization process, expressed as:

[0126]

[0127] Among them, t i represents the first boundary value, d0(r Ii) represents the first mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 0, d1(r Ii ) represents the distance of the second mapping point, i.e. the constellation diagram with the closest mapping point to the received signal being 1, where r Ii represents the i-th bit received value of the data on the first signal path after mapping under the current modulation format, where a is the unit amplitude of the modulation constellation diagram;

[0128] Performing a difference calculation on the first mapping point and the second mapping point to obtain first soft information;

[0129] The first soft information is expressed as:

[0130] LLR1=|d1(r Ii )-d0(r Ii )|

[0131] Among them, LLR1 represents the first soft information, d0(r Ii ) represents the first mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 0, d1(r Ii ) represents the distance of the second mapping point, that is, the constellation diagram with the mapping point closest to the received signal being 1;

[0132] quantizing the second boundary value to obtain a quantized second boundary value;

[0133] Determining a third mapping point whose distance from the received signal is a third preset value and a fourth mapping point whose distance from the received signal is a fourth preset value in the second boundary value after the quantization processing, expressed as:

[0134]

[0135] Among them, t j represents the second boundary value, d0(r Qi ) represents the third mapping point, which is the distance from the constellation diagram with the closest mapping point to the received signal being 0, d1(r Qi ) represents the fourth mapping point, i.e. the distance from the constellation diagram of the mapping point closest to the received signal is 1, where r Qi represents the i-th bit received value of the data on the second signal path after mapping under the current modulation format, where a is the unit amplitude of the modulation constellation diagram;

[0136] performing a difference calculation on the third mapping point and the fourth mapping point to obtain second soft information;

[0137] The second soft information is expressed as:

[0138] LLR2=|d1(r Qi)-d0(r Qi )|

[0139] Among them, LLR2 represents the second soft information, d0(r Qi ) represents the third mapping point, which is the distance from the constellation diagram with the closest mapping point to the received signal being 0, d1(r Qi ) represents the fourth mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 1.

[0140] Based on the same technical concept, corresponding to any of the above-mentioned embodiments and methods, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the soft information calculation method described in any of the above-mentioned embodiments is implemented.

[0141] Figure 3 10 is a schematic diagram showing a more specific hardware structure of an electronic device provided in this embodiment. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are communicatively connected to each other within the device via the bus 1050.

[0142] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0143] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage devices, dynamic storage devices, etc. The memory 1020 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0144] The input / output interface 1030 is used to connect input / output modules to implement information input and output. The input / output modules can be configured as components within the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. Input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc., and output devices may include a display, speaker, vibrator, indicator light, etc.

[0145] The communication interface 1040 is used to connect to a communication module (not shown) to enable communication between the device and other devices. The communication module can communicate via a wired method (such as USB, network cable, etc.) or a wireless method (such as mobile network, WiFi, Bluetooth, etc.).

[0146] The bus 1050 comprises a path for transmitting information between the various components of the device (eg, the processor 1010 , the memory 1020 , the input / output interface 1030 , and the communication interface 1040 ).

[0147] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may only include the components necessary to implement the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0148] The electronic device of the above embodiment is used to implement the corresponding soft information calculation method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0149] Based on the same technical concept, corresponding to any of the above-mentioned embodiments and methods, the present disclosure also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the soft information calculation method described in any of the above embodiments.

[0150] The computer-readable media of this embodiment include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0151] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the soft information calculation method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0152] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples. Within the scope of the present disclosure, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present disclosure as described above, which are not provided in detail for the sake of simplicity.

[0153] In addition, to simplify the description and discussion, and so as not to obscure the embodiments of the present disclosure, known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided figures. In addition, devices may be shown in the form of block diagrams to avoid obscuring the embodiments of the present disclosure, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present disclosure are to be implemented (i.e., these details should be fully within the purview of those skilled in the art). Where specific details (e.g., circuits) are set forth to describe exemplary embodiments of the present disclosure, it will be apparent to those skilled in the art that the embodiments of the present disclosure may be implemented without these specific details or with variations in these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0154] Although the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art based on the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0155] The embodiments of the present disclosure are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A method for calculating soft information, characterized in that: include: Obtain the received signal and constellation diagram of the communication system under the target modulation mode; Determine a first boundary value and a second boundary value of the modulation mode according to the received signal and the constellation diagram; Calculating first soft information and second soft information of the communication system under the target modulation mode based on the first boundary value and the second boundary value; The determining of the first boundary value and the second boundary value of the modulation mode according to the received signal and the constellation diagram includes: determining a first signal path and a second signal path of the received signal; Mapping the first signal path and the second signal path on the constellation diagram to obtain mapped first signal path and second signal path; establishing a coordinate system based on the mapped first signal path and the second signal path; The first boundary value and the second boundary value are determined according to the coordinate system.

2. The method according to claim 1, characterized in that The determining the first boundary value and the second boundary value according to the coordinate system includes: Determining a plurality of first constellation points on the mapped first signal path on a horizontal axis in the coordinate system, and taking an intermediate value between every two adjacent constellation points among the plurality of first constellation points as a first boundary value; A plurality of second constellation points on the mapped second signal path are determined on the vertical axis in the coordinate system, and an intermediate value between every two adjacent constellation points among the plurality of second constellation points is used as a second boundary value.

3. The method according to claim 2, characterized in that The calculating, based on the first boundary value, first soft information of the communication system under the target modulation mode includes: quantizing the first boundary value to obtain a quantized first boundary value; Determine a first mapping point in the first boundary value after the quantization process whose distance from the received signal is a first preset value and a second mapping point whose distance from the received signal is a second preset value; Performing a difference calculation on the first mapping point and the second mapping point to obtain first soft information; The first soft information is expressed as: LLR1=|d1(r Ii )-d0(r Ii )| Among them, LLR1 represents the first soft information, d0(r Ii ) represents the first mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 0, d1(r Ii ) represents the second mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 1.

4. The method according to claim 3, characterized in that The first boundary value is quantized to obtain the first boundary value after quantization, which is expressed as: Among them, t i represents the first boundary value, d0(r Ii ) represents the first mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 0, d1(r Ii ) represents the distance of the second mapping point, i.e. the constellation diagram with the closest mapping point to the received signal being 1, where r Ii represents the i-th bit received value of the data on the first signal path after mapping under the current modulation format, and a is the unit amplitude of the modulation constellation diagram.

5. The method according to claim 4, characterized in that The calculating, based on the second boundary value, second soft information of the communication system under the target modulation mode includes: quantizing the second boundary value to obtain a quantized second boundary value; Determine a third mapping point whose distance from the received signal is a third preset value and a fourth mapping point whose distance from the received signal is a fourth preset value in the second boundary value after the quantization process; performing a difference calculation on the third mapping point and the fourth mapping point to obtain second soft information; The second soft information is expressed as: LLR2=|d1(r Qi )-d0(r Qi )| Among them, LLR2 represents the second soft information, d0(r Qi ) represents the third mapping point, which is the distance from the constellation diagram with the closest mapping point to the received signal being 0, d1(r Qi ) represents the fourth mapping point, that is, the distance from the constellation diagram of the mapping point closest to the received signal is 1.

6. The method according to claim 5, characterized in that The second boundary value is quantized to obtain the quantized second boundary value, which is expressed as: Among them, t j represents the second boundary value, d0(r Qi ) represents the third mapping point, which is the distance from the constellation diagram with the closest mapping point to the received signal being 0, d1(r Qi ) represents the fourth mapping point, i.e. the distance from the constellation diagram of the mapping point closest to the received signal is 1, where r Qi represents the i-th bit received value of the data on the second signal path after mapping under the current modulation format, and a is the unit amplitude of the modulation constellation diagram.

7. A soft information computing device, characterized in that: include: The signal acquisition module is configured to: acquire a received signal and a constellation diagram of the communication system under a target modulation mode; A boundary value calculation module is configured to: determine a first boundary value and a second boundary value of the modulation mode according to the received signal and the constellation diagram; A soft information calculation module is configured to: calculate first soft information and second soft information of the communication system under the target modulation mode based on the first boundary value and the second boundary value; The determining of the first boundary value and the second boundary value of the modulation mode according to the received signal and the constellation diagram includes: determining a first signal path and a second signal path of the received signal; Mapping the first signal path and the second signal path on the constellation diagram to obtain mapped first signal path and second signal path; establishing a coordinate system based on the mapped first signal path and the second signal path; The first boundary value and the second boundary value are determined according to the coordinate system.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 6 is implemented. 9 . A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the method according to claim 1 .

Images