Signal processing method and apparatus, electronic device, and storage medium

Abstract

This application provides a signal processing method, apparatus, electronic device, and storage medium. The method includes: determining a signal to be processed for a current symbol, wherein the signal to be processed is a superimposed signal under multi-user multiplexing; performing modulation and coding scheme (MCS) detection on the signal to be processed to obtain a target modulation order for multi-user interference; performing demodulation processing on the signal to be processed according to the target modulation order to obtain usable signal components; and calculating the log-likelihood ratio (LLR) on the usable signal components to obtain an LLR result, wherein the LLR result is used to determine the original data corresponding to the signal to be processed. This approach decouples MCS detection and LLR calculation, filters usable signal components, and performs subsequent processing only on the usable signal components, avoiding calculations on the entire signal to be processed, thereby reducing redundant calculations and lowering the power consumption of signal processing.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a signal processing method, apparatus, electronic device and storage medium. Background Technology

[0002] In wireless communication scenarios involving multiple users, terminal devices receive superimposed signals and need to process these signals to obtain usable data.

[0003] In related technologies, signals are processed by coupling modulation and coding strategy detection with log-likelihood ratio calculation.

[0004] However, this method has high computational redundancy, which leads to high power consumption in signal processing. Summary of the Invention

[0005] This application provides signal processing methods, apparatus, electronic devices, and storage media to reduce power consumption during signal processing.

[0006] In a first aspect, embodiments of this application provide a signal processing method, comprising: determining a signal to be processed for a current symbol, wherein the signal to be processed is a superimposed signal under multi-user multiplexing; performing modulation and coding strategy (MCS) detection on the signal to be processed to obtain a target modulation order of multi-user interference; performing demodulation processing on the signal to be processed according to the target modulation order to obtain usable signal components; performing log-likelihood ratio (LLR) calculation on the usable signal components to obtain an LLR result, wherein the LLR result is used to determine the original data corresponding to the signal to be processed.

[0007] In one possible implementation, determining the signal to be processed for the current symbol includes: determining the resource bitmap corresponding to the current symbol; determining the set of valid resource blocks carrying multi-user multiplexing signals within the current symbol based on the resource bitmap; and determining the signal corresponding to the set of valid resource blocks as the signal to be processed.

[0008] In one possible implementation, the signal to be processed is subjected to modulation and coding strategy (MCS) detection to obtain the target modulation order of multi-user interference, including: identifying the signal to be processed through a serialized single-path search mechanism based on multiple preset modulation orders to obtain multiple correlation values, wherein the multiple correlation values ​​respectively represent the degree of matching between the signal to be processed and the corresponding modulation order; and determining the target modulation order from the multiple preset modulation orders based on the multiple correlation values.

[0009] In one possible implementation, determining the target modulation order from the plurality of preset modulation orders based on the plurality of correlation values ​​includes: normalizing the plurality of correlation values ​​to obtain a plurality of normalized correlation values; determining the maximum value of the plurality of normalized correlation values; and if the maximum value is greater than or equal to a preset threshold, determining the preset modulation order corresponding to the maximum value as the target modulation order.

[0010] In one possible implementation, the signal to be processed is demodulated according to the target modulation order to obtain usable signal components, including: determining signal reconstruction parameters of interference components in the signal to be processed according to the target modulation order; and reconstructing and separating the interference components from the signal to be processed according to the signal reconstruction parameters to obtain the usable signal components.

[0011] In one possible implementation, the process of reconstructing and separating the interference component from the signal to be processed according to the signal reconstruction parameters to obtain the usable signal component includes: reconstructing and separating the interference component from the signal to be processed according to the signal reconstruction parameters to obtain a separated signal; and performing noise filtering and signal purification processing on the separated signal to obtain the usable signal component.

[0012] In one possible implementation, performing a log-likelihood ratio (LLR) calculation on the available signal components to obtain an LLR result includes: determining a modulation mapping parameter corresponding to the target modulation order, wherein the modulation mapping parameter represents the correspondence rule between data bits and transmission symbols; performing a bit-by-bit LLR calculation on the available signal components according to the modulation mapping parameter to obtain a bit-level LLR result sequence corresponding to each data bit in the available signal components, wherein the bit-level LLR result sequence represents a set of values ​​representing the confidence level of each data bit value; and determining the bit-level LLR result sequence as the LLR result.

[0013] Secondly, embodiments of this application provide a signal processing apparatus, comprising: a determining module, configured to determine a signal to be processed for a current symbol, wherein the signal to be processed is a superimposed signal under multi-user multiplexing; a detection module, configured to perform modulation and coding strategy (MCS) detection on the signal to be processed to obtain a target modulation order of multi-user interference; a demodulation module, configured to perform demodulation processing on the signal to be processed according to the target modulation order to obtain usable signal components; and a calculation module, configured to perform log-likelihood ratio (LLR) calculation on the usable signal components to obtain an LLR result, wherein the LLR result is used to determine the original data corresponding to the signal to be processed.

[0014] In one possible implementation, the determining module is specifically configured to determine the resource bitmap corresponding to the current symbol; the determining module is further configured to determine the set of valid resource blocks carrying multi-user multiplexing signals within the current symbol based on the resource bitmap; the determining module is further configured to determine the signals corresponding to the set of valid resource blocks as signals to be processed.

[0015] In one possible implementation, the detection module is specifically used to identify the signal to be processed based on multiple preset modulation orders through a serialized single-path search mechanism, and obtain multiple correlation values, wherein the multiple correlation values ​​respectively represent the degree of matching between the signal to be processed and the corresponding modulation order; the detection module is further specifically used to determine the target modulation order from the multiple preset modulation orders based on the multiple correlation values.

[0016] In one possible implementation, the detection module is specifically used to normalize the plurality of correlation values ​​to obtain a plurality of normalized correlation values; the detection module is further used to determine the maximum value of the plurality of normalized correlation values; the detection module is further used to determine the preset modulation order corresponding to the maximum value as the target modulation order if the maximum value is greater than or equal to a preset threshold.

[0017] In one possible implementation, the demodulation module is specifically used to determine the signal reconstruction parameters of the interference components in the signal to be processed according to the target modulation order; the demodulation module is also specifically used to perform signal reconstruction and separation of the interference components from the signal to be processed according to the signal reconstruction parameters to obtain the usable signal components.

[0018] In one possible implementation, the demodulation module is specifically used to reconstruct and separate the interference component from the signal to be processed according to the signal reconstruction parameters to obtain a separated signal; the demodulation module is also specifically used to perform noise filtering and signal purification processing on the separated signal to obtain the usable signal component.

[0019] In one possible implementation, the apparatus further includes: a processing module, configured to determine modulation mapping parameters corresponding to the target modulation order, the modulation mapping parameters representing the correspondence rules between data bits and transmission symbols; the processing module is further configured to perform bit-by-bit LLR calculation on the available signal components according to the modulation mapping parameters, to obtain a bit-level LLR result sequence corresponding to each data bit in the available signal components, the bit-level LLR result sequence representing a set of values ​​representing the confidence level of each data bit value; the processing module is further configured to determine the bit-level LLR result sequence as the LLR result.

[0020] Thirdly, embodiments of this application provide a signal processing device, including: a memory and a processor;

[0021] The memory stores computer-executed instructions;

[0022] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0023] Fourthly, embodiments of this application provide a non-volatile computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0024] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0025] The signal processing method, apparatus, electronic device, and storage medium provided in this application include: determining a signal to be processed for a current symbol, wherein the signal to be processed is a superimposed signal under multi-user multiplexing; performing modulation and coding strategy (MCS) detection on the signal to be processed to obtain the target modulation order of multi-user interference; performing demodulation processing on the signal to be processed according to the target modulation order to obtain usable signal components; and performing log-likelihood ratio (LLR) calculation on the usable signal components to obtain an LLR result, wherein the LLR result is used to determine the original data corresponding to the signal to be processed. This scheme decouples MCS detection and LLR calculation, filters usable signal components, and performs subsequent processing only on the usable signal components, avoiding calculation on the entire signal to be processed, thereby reducing redundant calculations and lowering the power consumption of signal processing. Attached Figure Description

[0026] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0027] Figure 1 This is a schematic diagram illustrating an application scenario of a signal processing method provided in an embodiment of this application;

[0028] Figure 2 A schematic diagram of signal resource distribution provided in an embodiment of this application;

[0029] Figure 3 A schematic diagram illustrating tree search switching provided in an embodiment of this application;

[0030] Figure 4A schematic flowchart of a signal processing method provided in an embodiment of this application;

[0031] Figure 5 A schematic flowchart illustrating another signal processing method provided in an embodiment of this application;

[0032] Figure 6 A schematic diagram of the layered detection modulation method provided in the embodiments of this application;

[0033] Figure 7 A schematic diagram illustrating the decoupling of MCS detection and LLR calculation provided in an embodiment of this application;

[0034] Figure 8 This is a schematic diagram of the serial processing of MCS detection and LLR calculation provided in the embodiments of this application;

[0035] Figure 9 A schematic diagram illustrating resource scheduling where no RB occupies the symbols provided in this application embodiment;

[0036] Figure 10 A schematic diagram illustrating resource scheduling for symbols occupied by RBs, provided in an embodiment of this application;

[0037] Figure 11 This is a schematic diagram of the structure of a signal processing device provided in an embodiment of this application;

[0038] Figure 12 This is a schematic diagram of another signal processing device provided in an embodiment of this application;

[0039] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0040] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0041] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0042] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0043] It should be noted that the phrase "at...time" in the embodiments of this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; the embodiments of this application do not specifically limit this. Furthermore, the display interface provided in the embodiments of this application is merely an example, and the display interface may include more or less content.

[0044] It should be noted that the signal processing method, apparatus, electronic device and storage medium of this application can be used in the field of communication technology, or in any field other than communication. The application field of the signal processing method, apparatus, electronic device and storage medium of this application is not limited.

[0045] Figure 1 This is a schematic diagram illustrating an application scenario of a signal processing method provided in an embodiment of this application. An example is given based on the illustrated scenario: a terminal device receives a superimposed signal, processes the superimposed signal to obtain the original data, and then performs communication.

[0046] For example, in a multi-antenna multi-user multiple-input multiple-output (MU-MIMO) wireless communication system, network devices need to serve multiple terminal devices simultaneously, and there are unknown interference stream modulation methods (such as QPSK, 16QAM, etc.) between the terminal devices. The actual signal received by the terminal device is a superimposed signal including interference signals.

[0047] For example, in the signal transmitted by a network device, one user's data may be superimposed on another user's data, and the modulation method of the latter is unknown. The terminal device needs to process the received superimposed signal to obtain the original data transmitted by the network device.

[0048] In related technologies, superimposed signals are processed through multi-path parallel computing, that is, the complete process is run simultaneously for all possible modulation orders: simultaneously performing modulation and coding scheme (MCS) detection, demodulation, and log-likelihood ratio (LLR) calculation for QPSK; simultaneously performing MCS detection, demodulation, and LLR calculation for 16QAM; and simultaneously performing MCS detection, demodulation, and LLR calculation for 64QAM.

[0049] Furthermore, the coupled processing of MCS detection, demodulation, and LLR calculation results in a large computational load, which in turn leads to high power consumption in signal processing.

[0050] like Figure 2 As shown, Figure 2 This diagram illustrates the distribution of signal resources. In MU-MIMO transmission scenarios, the horizontal axis represents symbols in the time domain, and the vertical axis represents resource blocks (RBs) in the frequency domain. The squares formed by the horizontal and vertical axes represent the time-frequency resource units of each RB in each symbol. The resource units occupied by Single-User Multiple Input Multiple Output (SU-MIMO) transmission have no multi-user superposition interference, making them easier to process at the receiver. MU-MIMO transmissions, however, have resource units subject to unknown interference from multi-user signal superposition. The receiver must first analyze the modulation scheme of the interference signal before performing subsequent interference separation and signal detection. Invalid or unoccupied RBs indicate that there is no valid data transmission within the current symbol. Furthermore, different channels are adapted to different detection algorithms. For example, channels 0 and 2 are adapted to the minimum mean square error algorithm, suitable for scenarios with relatively controllable interference. Channel 1, on the other hand, is adapted to the robust MIMO detection algorithm, which can better handle channel estimation errors and multi-user interference, improving the stability of detection performance.

[0051] It can be seen that the first occurrence position of the effective RB in the time domain on different symbols is not fixed. This fine-grained, discontinuous and dynamically changing time-frequency distribution resource occupation pattern makes it impossible for terminal devices to uniformly process the full bandwidth resources. If a complete set of signal processing procedures such as MCS detection and demodulation is performed on each RB, a large amount of redundant calculation will be generated.

[0052] like Figure 3 As shown, Figure 3This diagram illustrates the tree search switching process. 2MUI indicates that the terminal device handles two layers of multi-user interference. 1MUI indicates that the terminal device handles two layers of multi-user interference. In both RB scheduling switching scenarios—2MUI to 1MUI / SU switching and 2MUI to 2MUI switching—two hardware processing paths, Tree Search #1 and Tree Search #2, are included for resolving the modulation order of the interference. In the 2MUI to 1MUI / SU switching scenario, Tree Search #1 performs modulation order detection on consecutive 2MUI type RB resources. Because the modulation method resolution of the two interference layers needs to be completed serially in the 2MUI scenario, the interference estimation of the second strongest interference layer must wait for the resolution result of the strongest interference layer. Therefore, when RB scheduling switches from 2MUI to 1MUI / SU, the processing pipeline experiences a disconnection at the switching node. When the first MUI modulation type is not empty and the tree search is idle, tree search #2 starts and takes over the subsequent RB resources of type 1MUI / SU. 1MUI only needs to handle one layer of multi-user interference, while SU does not have multi-user interference. Neither of them has a serial parsing dependency. Therefore, after time A, the processing flow of tree search #2 for 1MUI / SURB resources no longer experiences interruption, realizing the processing continuity from 2MUI to 1MUI / SU under RB-level scheduling.

[0053] In the 2MUI switching scenario, Tree Search #1 first performs modulation order parsing on the initial 2MUI type RB resources. Subsequent RB scheduling still maintains the 2MUI mode, with only RB occupation and release, no change in the number of interference layers, and no MU to SU switching. After the start-up conditions are met, Tree Search #2 starts and takes over the subsequent 2MUI type RB resources. Although 2MUI still needs to parse two layers of interference serially, because the number of interference layers has not changed, the processing pipelines of Tree Search #1 and Tree Search #2 remain continuous without any interruption. The tree search processing of RB resources exhibits a coherent pipeline characteristic.

[0054] It can be seen that tree search #1 is used to make an initial decision, and tree search #2 is used to accumulate the result of the previous symbol before making a decision. However, this causes the LLR of the first symbol to be discarded, which increases resource overhead.

[0055] The signal processing method provided in this application aims to solve the above-mentioned technical problems in related technologies.

[0056] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0057] Figure 4This is a flowchart illustrating a signal processing method provided in an embodiment of this application. The method includes the following steps:

[0058] S401. Determine the signal to be processed for the current symbol. The signal to be processed is a superimposed signal under multi-user multiplexing.

[0059] As an example, signal processing methods are applied to terminal devices, or chips or chip modules within terminal devices.

[0060] For example, the current symbol represents the single Orthogonal Frequency Division Multiplexing (OFDM) symbol currently in the wireless communication system, and is the smallest unit of time-domain scheduling.

[0061] With the example of the scenario, a single symbol is the minimum processing cycle. Since multi-user interference has the characteristic of dynamically changing with the symbol, processing symbol by symbol can ensure that the interference detection results are accurate in real time. At the same time, it avoids the hardware overhead caused by cross-symbol caching, reduces the cache depth, and avoids pipeline interruption problems caused by RB-level scheduling.

[0062] For example, in a MU-MIMO scenario where the superimposed signal is a linear superposition of multiple user signals, channel fading, and additive white Gaussian noise, the network device uses spatial multiplexing technology to map the transmission signals of at least two users to the same RB time-frequency resource unit for transmission.

[0063] S402. Perform modulation and coding strategy (MCS) detection on the signal to be processed to obtain the target modulation order of multi-user interference.

[0064] For example, MCS detection is a modulation order detection for multi-user interference layers, which focuses on detecting the modulation order of interfering user signals in the signal to be processed in order to eliminate interference.

[0065] For example, the target modulation order of multi-user interference represents the digital modulation order corresponding to each interference layer in the signal to be processed. For a 2MUI type RB, the target modulation order includes the modulation order of the strongest interference layer and the modulation order of the second strongest interference layer. For a 1MUI type RB, the target modulation order includes the modulation order of a single layer of interference.

[0066] For example, MCS detection is decoupled from LLR calculation, and the target modulation order is detected first within the current symbol reception period to obtain the target modulation order. By eliminating the parallel binding between MCS detection and subsequent processing, the pipeline does not need to operate at full load continuously, thereby reducing power consumption.

[0067] S403. Based on the target modulation order, demodulate the signal to be processed to obtain usable signal components.

[0068] For example, based on the target modulation order, the interference layer signal is reconstructed and eliminated from the signal to be processed to restore the usable signal components. The usable signal components are the target signal components that the network device only sends to the terminal device.

[0069] Optionally, based on the orthogonality of the MIMO channel matrix, spatial filtering is performed on the signal to be processed to initially separate the signal and obtain the signal components of each interference layer. According to the target modulation order, the corresponding constellation point mapping table is called (e.g., a 6-bit mapping relationship for 64QAM), and the interference components of each interference layer are reconstructed by combining the signal components of each interference layer. The signal to be processed and the interference components are then linearly subtracted to eliminate the multi-user interference components in the signal to be processed subcarrier by subcarrier, resulting in an intermediate signal after interference elimination.

[0070] For the intermediate signal, perform equalization processing using the minimum mean square error algorithm to eliminate residual channel fading and noise effects, and obtain usable signal components.

[0071] In related technologies, a complete set of hardware processing paths is configured in parallel for all possible modulation orders, resulting in high parallelism and high power consumption.

[0072] This application first obtains a unique target modulation order, and subsequent processing is only performed on the target modulation order, eliminating the need to retain multiple sets of parallel hardware paths, thereby reducing parallelism and power consumption.

[0073] S404. Calculate the log-likelihood ratio (LLR) for the available signal components to obtain the LLR result. The LLR result is used to determine the original data corresponding to the signal to be processed.

[0074] For example, LLR calculation is based on constellation point data of available signal components. It calculates the log-likelihood probability of each bit being "0" or "1". This is the core operation of soft decision. Unlike hard decision, soft decision can significantly improve the accuracy of channel decoding.

[0075] For example, the positive or negative value of the LLR result represents the probability tendency of the bit being "1" or "0", and the absolute value of the value represents the confidence level of the judgment. The LLR result is in the form of a one-dimensional bit stream and is the direct input to channel decoding.

[0076] For example, the channel decoder performs error correction decoding based on the LLR result, and finally restores the original data sent by the network device to the terminal device.

[0077] Based on the above implementation method, LLR calculation only depends on the demodulation output and is not directly coupled with MCS detection, resulting in a shorter pipeline and thus reducing the power consumption of signal processing.

[0078] The signal processing method provided in this application determines the signal to be processed for the current symbol, which is a superimposed signal under multi-user multiplexing; performs modulation and coding scheme (MCS) detection on the signal to be processed to obtain the target modulation order of multi-user interference; demodulates the signal to be processed according to the target modulation order to obtain usable signal components; calculates the log-likelihood ratio (LLR) on the usable signal components to obtain the LLR result, which is used to determine the original data corresponding to the signal to be processed. This scheme decouples MCS detection and LLR calculation, filters usable signal components, and only performs subsequent processing on the usable signal components, avoiding calculation on the entire signal to be processed, thereby reducing redundant calculations and lowering the power consumption of signal processing.

[0079] Based on any of the above embodiments, the following, in conjunction with Figure 5 The detailed process of signal processing is explained.

[0080] Figure 5 This is a schematic flowchart illustrating another signal processing method provided in an embodiment of this application. Figure 5 As shown, the method includes:

[0081] S501. Determine the signal to be processed for the current symbol. The signal to be processed is a superimposed signal under multi-user multiplexing.

[0082] One feasible implementation method is to determine the signal to be processed by: determining the resource bitmap corresponding to the current symbol; determining the set of valid resource blocks carrying multi-user multiplexing signals within the current symbol based on the resource bitmap; and determining the signal corresponding to the set of valid resource blocks as the signal to be processed.

[0083] For example, a resource bitmap is a binary bitmap in a communication system used to identify whether each RB in each OFDM symbol carries data and what type of data it carries. It is the core signaling for resource scheduling sent from higher-level protocols to terminal devices, and it is also the basis for terminal devices to accurately identify valid resources.

[0084] For example, the set of valid resource blocks refers to the set of all RBs marked as "carrying multi-user multiplexed signals" in the resource bitmap within the current symbol, excluding idle RBs, RBs carrying only single-user signals, faulty RBs, or invalid RBs.

[0085] For example, the flag bits corresponding to each RB in the bitmap are traversed. RBs with the flag bit set to "carry multi-user multiplexing signal" are selected. Idle RBs, SU signal RBs, and invalid RBs are removed, and only RBs that need to perform multi-user interference processing are retained, thus forming a set of valid resource blocks.

[0086] In this feasible implementation, only valid Resource Blocks (RBs) carrying multi-user multiplexed signals are retained through resource bitmap filtering, and subsequent processing is performed only on these RBs. This avoids performing invalid MCS detection, demodulation, and other operations on RBs without multi-user interference, thereby reducing unnecessary computation and lowering the power consumption of signal processing.

[0087] S502. Based on multiple preset modulation orders, the signal to be processed is identified through a serialized single-path search mechanism to obtain multiple correlation values. The multiple correlation values ​​represent the degree of matching between the signal to be processed and the corresponding modulation order.

[0088] For example, the preset modulation order is a pre-configured set of standard modulation orders supported by multi-user interference.

[0089] For example, by serializing a single path, all preset modulation orders are traversed sequentially to perform feature matching on the multi-user interference components in the signal to be processed. After each modulation order matching calculation is completed, a corresponding correlation value is output, and finally a set of correlation values ​​with the same number of preset modulation orders is obtained.

[0090] The correlation value is used to quantify the degree of matching between the multi-user interference component in the signal to be processed and a certain preset modulation order. The larger the correlation value, the more the multi-user interference component matches the characteristics of the modulation order.

[0091] With the example of the scenario, the serialized single-path search mechanism uses only one hardware detection path to match and identify each candidate modulation order in a preset order, rather than using multiple hardware paths to detect in parallel at the same time.

[0092] Optionally, during the traversal, if a relevant value exceeding the relevant value threshold is matched, the matching process stops to improve matching efficiency.

[0093] Based on the above implementation method, the detection process only occupies a single hardware path and there is no parallel multi-path detection logic, thereby reducing the power consumption of signal processing.

[0094] S503. Determine the target modulation order from multiple preset modulation orders based on multiple relevant values.

[0095] For example, from multiple correlation values, the preset modulation order with the largest correlation value (i.e. the highest degree of matching) is selected as the target modulation order for this detection.

[0096] S504. Normalize multiple correlation values ​​to obtain multiple normalized correlation values.

[0097] For example, the original correlation values ​​can be affected by fluctuations in received signal power, channel fading, and uneven noise intensity. The amplitude ranges of correlation values ​​corresponding to different modulation orders are inconsistent and the dimensions are not uniform, making direct horizontal comparison impossible.

[0098] For example, multiple correlation values ​​are mapped to a unified quantization range (e.g., [0,1]) to eliminate interference from mismatched features such as signal amplitude and channel gain, so that the processed normalized correlation values ​​retain only the core feature of the degree of matching between the signal and the modulation order.

[0099] Optionally, normalization can be performed using methods such as amplitude normalization, energy normalization, or peak normalization.

[0100] S505. Determine the maximum value of multiple normalized correlation values.

[0101] For example, by using a serial traversal comparison method, all normalized correlation values ​​are compared one by one, and the larger value at each step is retained to finally obtain the global maximum value.

[0102] For example, the preset modulation order corresponding to the maximum value is the modulation order with the highest feature matching degree of multi-user interference components in the signal to be processed, and is a candidate value for the target modulation order.

[0103] S506. If the maximum value is greater than or equal to the preset threshold, then the preset modulation order corresponding to the maximum value is determined as the target modulation order.

[0104] For example, the preset threshold is a pre-configured validity decision threshold, which can be obtained through simulation and experimental calibration. The preset threshold is used to distinguish between valid multi-user interference matching results and false matching results generated by noise, spurious signals, and invalid signals.

[0105] For example, if the maximum value is greater than or equal to a preset threshold, the current MCS detection is determined to be a valid detection, and the modulation order corresponding to the maximum value is the actual multi-user interference modulation order.

[0106] For example, if the maximum value is less than the preset threshold, it is determined that there is no effective multi-user interference or the detection result is a noise mismatch, and the effective target modulation order is not output, and the subsequent redundancy processing is terminated directly.

[0107] Below, in conjunction with Figure 6 The layered detection modulation method is explained.

[0108] Figure 6 This is a schematic diagram of a layered detection modulation method provided in an embodiment of this application. Figure 6As shown, in a scenario with 2MU-MIMO, 1 resource block (1RB), and 4 resource elements (4REs), tree search #1 corresponds to the strongest interference layer, and tree search #2 corresponds to the second strongest interference layer. There are two serial stages with no parallel execution. In tree search #1, four REs within the 1RB are input, each pre-configured with four candidate modulation orders: QPSK, 16QAM, 64QAM, and 256QAM. For each RE, all candidate modulation orders are traversed, and multiple correlation values ​​are calculated. The correlation values ​​calculated for REs 0-RE3 are stored in memory to temporarily store and summarize intermediate results. Based on the summarized correlation values ​​in memory, the modulation scheme of the strongest interference layer is determined. In tree search #2, the calculation logic of tree search #1 is reused, and for each RE, the candidate modulation orders are traversed again, multiple correlation values ​​are calculated, and stored in memory. Based on the memory results, the modulation scheme of the second strongest interference layer is determined.

[0109] Based on the above implementation methods, normalization processing eliminates the interference of channel fading and signal power fluctuations on correlation values, making the modulation order decision depend only on the inherent matching characteristics of the signal and modulation method, avoiding detection deviations caused by channel time-varying, thereby improving the reliability of signal processing.

[0110] S507. Based on the target modulation order, demodulate the signal to be processed to obtain usable signal components.

[0111] One feasible implementation method is to perform demodulation processing by: determining the signal reconstruction parameters of the interference components in the signal to be processed according to the target modulation order; and reconstructing and separating the interference components from the signal to be processed according to the signal reconstruction parameters to obtain the usable signal components.

[0112] For example, the interference component is the multi-user interference component generated by other users in the signal to be processed.

[0113] For example, the signal reconstruction parameters are the core parameter set for restoring the interference components, which are directly derived from the target modulation order. Specifically, they include: the constellation point mapping rules corresponding to the target modulation order (e.g., QPSK corresponds to the coordinate mapping of 4 constellation points, 64QAM corresponds to the coordinate mapping of 64 constellation points), the signal amplitude threshold of the interference components, the phase compensation parameters, and the symbol rate matching parameters, all of which correspond one-to-one with the target modulation order.

[0114] Optionally, the signal reconstruction parameters corresponding to the target modulation order can be determined by looking up a table, eliminating the need for complex calculations and thus reducing power consumption.

[0115] For example, during the reconstruction process, the signal waveform corresponding to the interference component is constructed according to the signal reconstruction parameters and the sign rules corresponding to the modulation order.

[0116] Optionally, if it is multi-layer interference (2MUI), the interference signals of each layer are reconstructed serially, and the reconstruction of each layer of interference is completed in turn.

[0117] For example, by subtracting the signal to be processed from the reconstructed interference component subtracting it from the signal to be processed subcarrier by subcarrier through linear subtraction, lightweight MMSE (minimum mean square error) equalization is performed on the subtracted signal component to eliminate residual noise and interference terms, and finally obtain the usable signal component.

[0118] With the example of the scenario, the available signal components are frequency domain constellation point data, which only contain the effective transmission data of the target user and have no multi-user interference components.

[0119] In this feasible implementation, the demodulation process uses the target modulation order of the MCS detection output, which does not need to be executed in parallel with the MCS detection or share hardware resources with the MCS detection, thus decoupling the MCS detection and demodulation and reducing the power consumption of signal processing.

[0120] One feasible implementation method is to reconstruct and separate the interference components from the signal to be processed according to the signal reconstruction parameters to obtain the separated signal; and to perform noise filtering and signal purification processing on the separated signal to obtain the usable signal components.

[0121] For example, the waveform reconstruction of the interference component is completed according to the signal reconstruction parameters, and the reconstructed interference component is removed from the signal to be processed by the multi-user multiplexing, so as to achieve the initial separation of the usable signal component and the interference component, and output the separated signal of the residual noise component.

[0122] For example, by using digital signal processing, lightweight noise filtering and purification are performed on the separated signals to obtain usable signal components that meet the requirements of LLR calculation.

[0123] In this feasible implementation, the demodulation process is divided into two independent serial sub-steps: preliminary interference separation and noise filtering and purification. Each stage is executed in a time-sharing manner without the need for parallel operation, thereby reducing the dynamic power consumption of the hardware working simultaneously.

[0124] S508. Calculate the log-likelihood ratio (LLR) for the available signal components to obtain the LLR result. The LLR result is used to determine the original data corresponding to the signal to be processed.

[0125] Below, in conjunction with Figure 7 The decoupled MCS detection and LLR calculation are explained.

[0126] Figure 7 This is a schematic diagram illustrating the decoupled MCS detection and LLR calculation provided in an embodiment of this application. Figure 7As shown, the structure includes three dimensions: layers represent different levels of multi-user interference (e.g., layer 0 is the strongest interference layer, and layer 1 is the second strongest interference layer); bits represent the bits corresponding to the modulation order of each interference layer (e.g., b0-b9), used to traverse candidate combinations of modulation orders bit by bit; and paths represent candidate branches of the tree search, with different paths corresponding to different candidate combinations of modulation orders. By traversing the paths, the correlation value between each combination and the signal to be processed can be calculated.

[0127] In related technologies, MCS detection is coupled with LLR calculation. Figure 7 Parallel computation is performed simultaneously in both the path and bit dimensions. Each path (path 0, path 1, ..., path N-1) is independently configured with a complete hardware path, performing two tasks concurrently: MCS detection of the interfering signal and LLR calculation of the target user signal. This means that the number of hardware paths increases linearly with the number of paths, leading to increased resource overhead. In the bit dimension, each path performs parallel computation on all bits (b0-b9) simultaneously during processing. This is used for constellation point matching in the MCS detection stage (determining the modulation order of the interference) and for bit-by-bit decision-making in the LLR calculation stage (generating the confidence level of each bit). This full-bit parallelism further increases power consumption.

[0128] This application limits the interference layer range through hierarchical design and traverses candidate modulation orders via multiple paths. At the path dimension, parallelism is preserved (different paths can handle different RBs or interference layers), but only lightweight tree search is performed. At the bit dimension, only necessary bits are traversed (e.g., b0-b1 for QPSK, b0-b3 for 16QAM) to quickly determine the target modulation order for multi-user interference; LLR calculation is not performed at this stage. After determining the target modulation order, it is processed in a SU-MIMO manner. At the bit dimension, LLR calculation is performed only for the bits corresponding to the target modulation order (e.g., b0~b5 for 64QAM), eliminating the need for hardware configuration for parallel processing of other modulation orders. In this case, hardware pressure is concentrated only at the path dimension (i.e., different paths process different RBs), and multi-path parallelism at the bit dimension is completely eliminated.

[0129] Below, in conjunction with Figure 8 The serial processing of MCS detection and LLR calculation is explained.

[0130] Figure 8 This is a schematic diagram illustrating the serial processing of MCS detection and LLR calculation provided in an embodiment of this application. Figure 8As shown, the input consists of four RE signals within one RB, carrying a superposition of the target user signal and multi-user interference. In tree search #1, for each RE, 20 candidate paths are traversed, each path corresponding to a candidate modulation order combination. The correlation between each path and the signal to be processed is calculated to evaluate the degree of matching between the modulation order corresponding to the path and the actual interference. Based on the correlation, combined with a preset threshold or maximum value filtering rule, invalid paths with low correlation are eliminated, and the optimal path with the highest correlation is selected. Based on the optimal path, the target modulation order of the current interference layer is determined. Based on the determined target modulation order, LLR calculation is performed on each RE. The LLR calculation of SU-MIMO can be reused, thereby reducing the power consumption of signal processing.

[0131] One feasible implementation method involves performing LLR calculation as follows: determining the modulation mapping parameters corresponding to the target modulation order, where the modulation mapping parameters represent the correspondence rules between data bits and transmission symbols; performing bit-by-bit LLR calculation on the available signal components based on the modulation mapping parameters to obtain a bit-level LLR result sequence corresponding to each data bit in the available signal components, where the bit-level LLR result sequence represents the set of values ​​representing the confidence level of each data bit value; and determining the bit-level LLR result sequence as the LLR result.

[0132] For example, modulation mapping parameters are a set of parameters that characterize the correspondence between data bits (0 or 1) and transmission symbols (constellation points), and are the core benchmark for LLR calculation. The modulation mapping rules corresponding to the target modulation order can be determined by looking up a table.

[0133] For example, based on the modulation mapping parameters, for each transmission symbol in the available signal components, LLR calculations are performed sequentially in bit order (i.e., the LLR value of the first bit is calculated first, then the second bit, and so on, completing all bit operations in sequence). The LLR calculation for each bit depends only on the modulation mapping rule corresponding to the current bit, without multi-bit parallel operations, and finally outputs a sequence of bit-level LLR results arranged in bit order.

[0134] With the example of the scenario, channel decoding can be performed based on the LLR result to restore the original data.

[0135] Below, in conjunction with Figure 9 The resource scheduling for symbols where no RB occupies the resource is explained.

[0136] Figure 9 This is a schematic diagram illustrating resource scheduling where no RB is occupied, as provided in the embodiments of this application. For example... Figure 9As shown, in a scenario where no RB is occupied (i.e., all RBs are idle), S0 and S1 represent two consecutive symbols, and RB0-RB3 represent RB indices. Different delays are configured for different processing flows based on the clock CLK. For example, signal processing has a delay of 70 clock cycles, channel estimation has a delay of 90 clock cycles, MCS detection has a delay of 60 clock cycles, interference decision has a delay of 18 clock cycles, and LLR calculation has a delay of 60 clock cycles. In MCS detection, RB0, RB1, RB2, and RB3 are scheduled sequentially, and the MCS results for each RB are output. After the MCS detection process is completed, it restarts from RB0, reusing the same pipeline to output the LLR results for each RB. Because the RB resources are all idle, there are no scheduling conflicts, the pipeline can run completely serially without interruption, ensuring computational efficiency.

[0137] Below, in conjunction with Figure 10 The resource scheduling for symbols occupied by RB is explained.

[0138] Figure 10 This is a schematic diagram illustrating the resource scheduling of symbols occupied by RBs, as provided in an embodiment of this application. Figure 10 As shown, within symbol S0, RB1 and RB2 are occupied. Within symbol S0, RB0 and RB3 undergo MCS detection sequentially. After MCS detection, the same pipeline is reused to output the LLR results of RB0 and RB3. In symbol S1, RB1 and RB2 have been released. Since they belong to MU RB resources, RB1 and RB2 need to be scheduled as MU RBs first to obtain their corresponding MCS values ​​before overall SU RB scheduling. The entire scheduling process is consistent with symbol 0, only the corresponding MU RB positions are different.

[0139] In this feasible implementation, LLR calculation relies only on the pre-determined target modulation order and available signal components, and is completely decoupled from the MCS detection and demodulation stages, avoiding dynamic power consumption caused by parallel processing, while reducing the static power consumption of hardware control logic, thereby reducing the power consumption of signal processing.

[0140] Figure 11 This is a schematic diagram of a signal processing device provided in an embodiment of this application. Figure 11 As shown, the signal processing device 110 may include: a determination module 111, a detection module 112, a demodulation module 113, and a calculation module 114.

[0141] The determination module 111 is used to determine the signal to be processed for the current symbol. The signal to be processed is a superimposed signal under multi-user multiplexing.

[0142] Detection module 112 is used to perform modulation and coding strategy (MCS) detection on the signal to be processed to obtain the target modulation order of multi-user interference;

[0143] Demodulation module 113 is used to demodulate the signal to be processed according to the target modulation order to obtain usable signal components;

[0144] The calculation module 114 is used to calculate the log-likelihood ratio (LLR) of the available signal components to obtain the LLR result, which is used to determine the original data corresponding to the signal to be processed.

[0145] Optionally, module 111 can be executed. Figure 4 S401 in the embodiment.

[0146] Optionally, the detection module 112 can perform... Figure 4 S402 in the embodiment.

[0147] Optionally, demodulation module 113 can perform... Figure 4 S403 in the embodiment.

[0148] Optionally, the calculation module 114 can perform... Figure 4 S404 in the embodiment.

[0149] It should be noted that the signal processing device shown in the embodiments of this application can execute the technical solutions shown in the above method embodiments, and its implementation principle and beneficial effects are similar, so they will not be described again here.

[0150] In one possible implementation, the determining module 111 is specifically used for:

[0151] Determine the resource bitmap corresponding to the current symbol;

[0152] Based on the resource bitmap, determine the set of valid resource blocks carrying multi-user multiplexing signals within the current symbol;

[0153] The signals corresponding to the set of valid resource blocks are identified as signals to be processed.

[0154] In one possible implementation, the detection module 112 is specifically used for:

[0155] Based on multiple preset modulation orders, the signal to be processed is identified through a serialized single-path search mechanism, and multiple correlation values ​​are obtained. These multiple correlation values ​​represent the degree of matching between the signal to be processed and the corresponding modulation order.

[0156] The target modulation order is determined from multiple preset modulation orders based on multiple relevant values.

[0157] In one possible implementation, the detection module 112 is specifically used for:

[0158] Multiple correlation values ​​are normalized to obtain multiple normalized correlation values;

[0159] Determine the maximum value of multiple normalized correlation values;

[0160] If the maximum value is greater than or equal to the preset threshold, then the preset modulation order corresponding to the maximum value is determined as the target modulation order.

[0161] In one possible implementation, the demodulation module 113 is specifically used for:

[0162] Based on the target modulation order, determine the signal reconstruction parameters of the interference components in the signal to be processed;

[0163] Based on the signal reconstruction parameters, the interference components are reconstructed and separated from the signal to be processed to obtain the usable signal components.

[0164] In one possible implementation, the demodulation module 113 is specifically used for:

[0165] Based on the signal reconstruction parameters, the interference components are reconstructed and separated from the signal to be processed to obtain the separated signal.

[0166] The separated signals are subjected to noise filtering and signal purification processes to obtain usable signal components.

[0167] Figure 12 This is a schematic diagram of another signal processing device provided in an embodiment of this application. Figure 11 Based on the illustrated embodiments, as Figure 12 As shown, the signal processing device 110 also includes a processing module 115.

[0168] Processing module 115 is used for:

[0169] Determine the modulation mapping parameters corresponding to the target modulation order. The modulation mapping parameters represent the correspondence rules between data bits and transmission symbols.

[0170] Based on the modulation mapping parameters, bit-by-bit LLR calculation is performed on the available signal components to obtain the bit-level LLR result sequence corresponding to each data bit in the available signal components. The bit-level LLR result sequence represents the set of numerical values ​​representing the confidence level of each data bit value.

[0171] The sequence of bit-level LLR results is identified as the LLR result.

[0172] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 13 As shown, the electronic device includes:

[0173] The electronic device includes a processor 291 and a memory 292; it may also include a communication interface 293 and a bus 294. The processor 291, memory 292, and communication interface 293 can communicate with each other via the bus 294. The communication interface 293 can be used for information transmission. The processor 291 can invoke logical instructions stored in the memory 292 to execute the methods of the above embodiments.

[0174] Furthermore, the logic instructions in the aforementioned memory 292 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0175] The memory 292, as a non-volatile computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this application. The processor 291 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 292, that is, it implements the methods in the above-described method embodiments.

[0176] The memory 292 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 292 may include high-speed random access memory and may also include non-volatile memory.

[0177] This application provides a non-volatile computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in the foregoing embodiments.

[0178] This application provides a computer program product, including a computer program that, when executed by a processor, implements the method as described in the foregoing embodiments.

[0179] This application provides a chip, which includes at least one processor and an interface circuit. The interface circuit and the at least one processor are connected, and the processor executes the method of the aforementioned embodiment by running program instructions.

[0180] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0181] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps; they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages, which do not necessarily complete at the same time but can be executed at different times. The execution order of these sub-steps or stages is also not necessarily sequential but can be alternated or carried out in turn with other steps or at least some of the sub-steps or stages of other steps.

[0182] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0183] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0184] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. The processor can be any suitable hardware processor, such as CPU, GPU, FPGA, DSP, and ASIC. The storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0185] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0186] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0187] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0188] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A signal processing method, characterized in that, include: Determine the signal to be processed for the current symbol, wherein the signal to be processed is a superimposed signal under multi-user multiplexing; The signal to be processed is subjected to modulation and coding strategy (MCS) detection to obtain the target modulation order of multi-user interference; Based on the target modulation order, the signal to be processed is demodulated to obtain usable signal components; The available signal components are subjected to log-likelihood ratio (LLR) calculation to obtain the LLR result, which is used to determine the original data corresponding to the signal to be processed.

2. The method according to claim 1, characterized in that, Determine the signal to be processed for the current symbol, including: Determine the resource bitmap corresponding to the current symbol; Based on the resource bitmap, determine the set of valid resource blocks carrying multi-user multiplexing signals within the current symbol; The signal corresponding to the set of valid resource blocks is determined as the signal to be processed.

3. The method according to claim 1, characterized in that, The signal to be processed is subjected to modulation and coding scheme (MCS) detection to obtain the target modulation order of multi-user interference, including: Based on multiple preset modulation orders, the signal to be processed is identified through a serialized single-path search mechanism to obtain multiple correlation values, which respectively represent the degree of matching between the signal to be processed and the corresponding modulation order. The target modulation order is determined from the plurality of preset modulation orders based on the plurality of relevant values.

4. The method according to claim 3, characterized in that, Determining the target modulation order from the plurality of preset modulation orders based on the plurality of relevant values ​​includes: The multiple correlation values ​​are normalized to obtain multiple normalized correlation values; Determine the maximum value of the plurality of normalized correlation values; If the maximum value is greater than or equal to a preset threshold, then the preset modulation order corresponding to the maximum value is determined as the target modulation order.

5. The method according to claim 1, characterized in that, Based on the target modulation order, the signal to be processed is demodulated to obtain usable signal components, including: Based on the target modulation order, determine the signal reconstruction parameters of the interference components in the signal to be processed; Based on the signal reconstruction parameters, the interference component is reconstructed and separated from the signal to be processed to obtain the usable signal component.

6. The method according to claim 5, characterized in that, Based on the signal reconstruction parameters, the interference components are reconstructed and separated from the signal to be processed to obtain the usable signal components, including: Based on the signal reconstruction parameters, the interference component is reconstructed and separated from the signal to be processed to obtain a separated signal; The separated signal is subjected to noise filtering and signal purification processing to obtain the usable signal component.

7. The method according to any one of claims 1-6, characterized in that, The log-likelihood ratio (LLR) is calculated for the available signal components to obtain the LLR result, including: Determine the modulation mapping parameters corresponding to the target modulation order, wherein the modulation mapping parameters represent the correspondence rules between data bits and transmission symbols; According to the modulation mapping parameters, bit-by-bit LLR calculation is performed on the available signal components to obtain a bit-level LLR result sequence corresponding to each data bit in the available signal components. The bit-level LLR result sequence represents a set of numerical values ​​representing the confidence level of each data bit value. The bit-level LLR result sequence is determined as the LLR result.

8. A signal processing apparatus, characterized in that, include: The determination module is used to determine the signal to be processed for the current symbol, wherein the signal to be processed is a superimposed signal under multi-user multiplexing; The detection module is used to perform modulation and coding strategy (MCS) detection on the signal to be processed to obtain the target modulation order of multi-user interference. The demodulation module is used to demodulate the signal to be processed according to the target modulation order to obtain usable signal components; The calculation module is used to perform log-likelihood ratio (LLR) calculation on the available signal components to obtain the LLR result, which is used to determine the original data corresponding to the signal to be processed.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-7.

10. A non-volatile computer-readable storage medium, characterized in that, The non-volatile computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

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