Two-step detection method, system and device based on maximum likelihood criterion

Abstract

The invention discloses a two-step detection method, system and device based on a maximum likelihood criterion, and belongs to the technical field of wireless communication, and the method comprises the steps: carrying out the detection and sorting of all possible symbol constellation combinations through a maximum likelihood detection algorithm, and selecting the symbol constellation combination with the minimum distance value as a preliminary decoding result based on the maximum likelihood criterion, completing the first-step detection; step 2, setting a detection threshold value, finding all other distance values of which the difference value with the distance value corresponding to the initial decoding result is within the range of the detection threshold value based on the sequence of the distance values obtained in the step 1, and storing the corresponding symbol constellation combination in an alternative set; and adopting a measurement standard different from the maximum likelihood detection algorithm of the first-step detection, and carrying out second-step detection on the symbol constellation combinations in the alternative set based on the maximum likelihood criterion, and finding out the symbol constellation combination with the minimum measurement value as a target decoding signal. According to the method, the problem of an error code platform is solved, and the decoding accuracy and reliability are effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a two-step detection method, system and device based on a maximum likelihood criterion. Background Art

[0002] With the continuous development of wireless communications, limited spectrum resources have gradually become a bottleneck to meet the growing demand for communication capacity. Multiple-Input Multiple-Output (MIMO) technology can achieve higher data throughput and communication quality without increasing the transmission power or system bandwidth by spatially multiplexing multiple data streams to multiple users (MU). It is widely regarded as a promising wireless communication technology. Despite this, MU-MIMO systems face many challenges in practical applications. Among them, multi-user interference is an important factor that seriously restricts wireless transmission performance and needs to be handled by precoding technology.

[0003] From a traditional point of view, interference is generally considered to be a harmful factor that limits the performance of wireless communication systems, and most existing linear precoding schemes still aim to suppress or eliminate interference. These traditional precoding schemes often rely only on precoding weight matrices designed based on channel state information, without considering data symbol information. In contrast, the interference-utilization-based symbol-level precoding (SLP) scheme can convert interference signals that are not conducive to wireless transmission into useful signals by adaptively adjusting the amplitude and phase of the interference signal using channel state information and additional data symbol information. This not only fully solves the multi-user interference problem in the downlink transmission of the MU-MIMO system, but also can use the power of the interference signal to improve the energy efficiency of the system, thereby providing significant performance gains.

[0004] It is worth noting that in the downlink transmission process of the MU-MIMO system, when multi-level modulation is used, such as high-order quadrature amplitude modulation (QAM), for the symbol-level transmission precoding processing based on interference utilization at the base station, the traditional maximum likelihood detection (MLD) receiver will have a more serious "error platform" during the decoding process. This is mainly because in the complex signal space, although the traditional MLD algorithm attempts to directly determine the original transmitted signal in a decoding operation, it often encounters multiple candidate signals with similar detection results, which makes these signals easily confused during detection, resulting in decoding errors. Summary of the invention

[0005] The purpose of the present invention is to provide a two-step detection method, system and device based on the maximum likelihood criterion, which aims to solve the "error platform" problem encountered in the downlink transmission of the MU-MIMO system under high-order modulation based on interference utilization symbol-level transmission precoding, effectively improve the accuracy and reliability of decoding, and further improve the communication performance of the system.

[0006] In order to achieve the above object, the present invention has the following technical solutions: In a first aspect, a two-step detection method based on a maximum likelihood criterion is provided, comprising: All possible symbol constellation combinations are detected and sorted by the maximum likelihood detection algorithm, and based on the maximum likelihood criterion, the symbol constellation combination with the smallest distance value is selected as the preliminary decoding result to complete the first step of detection; Set a detection threshold, sort the distance values ​​obtained in the first detection step, find all other distance values ​​whose difference with the distance value corresponding to the preliminary decoding result is within the detection threshold, and store the corresponding symbol constellation combination in the candidate set; A metric different from the maximum likelihood detection algorithm in the first step is used, and the symbol constellation combination in the candidate set is detected in the second step based on the maximum likelihood criterion to find the symbol constellation combination with the smallest metric value as the target decoding signal.

[0007] As a preferred solution, the two-step detection method based on the maximum likelihood criterion is applicable to a multi-stream MU-MIMO downlink system, wherein the multi-stream MU-MIMO downlink system includes a A base station with 1 transmitting antenna, and multi-antenna user terminals, each equipped with receiving antennas and meet ; The user The number of received data streams is recorded as ,satisfy , the modulated input signal at the base station is expressed as:

[0008] in, Indicates that it will be sent to the user symbolic data stream; When the number of user receiving antennas is greater than the received data stream, the original channel cannot be used directly to solve the precoding matrix.

[0009] As a preferred solution, the two-step detection method based on the maximum likelihood criterion also includes applying singular value decomposition to the user's channel matrix to obtain an equivalent channel matrix, combining the equivalent channel matrices of all users to obtain the equivalent channel of the MU-MIMO system; and using the equivalent channel of the MU-MIMO system to calculate the symbol-level transmit precoding matrix.

[0010] As a preferred solution, applying singular value decomposition to the channel matrix of the user to obtain an equivalent channel matrix, combining the equivalent channel matrices of all users, and obtaining the equivalent channel of the MU-MIMO system includes the following steps: Press the button to the user The channel matrix Using singular value decomposition:

[0011] in, yes The singular value matrix of and are all unitary matrices; User-based Number of received data streams right Divide into blocks, and the dimensions are and The two sub-matrices of and , the expression is as follows:

[0012] In the above formula Corresponds to The submatrix composed of the largest singular value vector of The user The equivalent channel matrix Constructed, the expression is as follows:

[0013] All users Combined to get the equivalent channel of the entire MU-MIMO system , at this time, the original MU-MIMO system is equivalent to a channel matrix Low-dimensional MU-MIMO system.

[0014] As a preferred scheme, the two-step detection method based on the maximum likelihood criterion also includes constructing a symbol-level transmit precoding optimization problem based on interference utilization under the constraint of the total available transmit power of the base station through an equivalent channel of the MU-MIMO system, obtaining a symbol-level transmit precoding matrix by solving the symbol-level transmit precoding optimization problem based on interference utilization, and obtaining the precoded signal of the base station according to the symbol-level transmit precoding matrix.

[0015] As a preferred solution, the equivalent channel of the MU-MIMO system is used to construct a symbol-level transmit precoding optimization problem based on interference utilization under the constraint of the total available transmit power of the base station, including the following steps: For 16QAM modulation, for the constellation points considered Decomposing along the direction of the detection threshold, we get:

[0016] For User's The decoded signal stream is decomposed along the direction of the detection threshold, and the following is obtained:

[0017] In the formula, as well as These are two new column vectors introduced in the 16QAM constellation; and are two detection thresholds parallel to each constellation point; and are two real scaling factors, indicating the severity of the interference on the decoded signal stream; Users, the above formula is expressed in a compact form as follows:

[0018] The 16QAM constellation points are decomposed into two sets, where Represents the constellation point that can be used for interference. If the noise-free decoded signal stream is located in the constructive area, the following expression is satisfied:

[0019] When designing a precoding matrix based on interference utilization, the only interference that the base station can utilize is the interference between data streams within the user, and the interference between users is set to zero, that is, the following expression is satisfied:

[0020] The symbol-level transmit precoding optimization problem based on interference utilization is expressed as follows:

[0021] In the formula, Indicates the total available transmit power of the base station; The method of obtaining a symbol-level transmit precoding matrix by solving a symbol-level transmit precoding optimization problem based on interference utilization, and obtaining a precoded signal of a base station according to the symbol-level transmit precoding matrix comprises the following steps: The convex optimization toolbox is used to solve the symbol-level transmit precoding optimization problem based on interference utilization, and the symbol-level transmit precoding matrix is ​​obtained. , and obtain the output signal after precoding processing at the base station :

[0022] Based on the above settings, The received signal of a user It is expressed as follows:

[0023] In the formula, Indicates base station and user The channel matrix between Each term in follows a standard complex Gaussian distribution; The mean value at the receiving end is , the variance is Additive white Gaussian noise vector.

[0024] As a preferred solution, the method of detecting and sorting all possible symbol constellation combinations by using a maximum likelihood detection algorithm, and selecting a symbol constellation combination with a minimum distance value as a preliminary decoding result based on a maximum likelihood criterion, and completing the first step of detection includes the following steps: The maximum likelihood detection algorithm is used to detect all The possible symbol constellation combinations are sorted by distance value, and based on the maximum likelihood criterion, the signal corresponding to the minimum distance value is selected As a preliminary decoding result, the calculation expression is as follows: .

[0025] As a preferred solution, the method adopts a metric different from the maximum likelihood detection algorithm in the first step, and performs a second step detection on the symbol constellation combination in the candidate set based on the maximum likelihood criterion, and finds the symbol constellation combination with the smallest metric value as the target decoding signal, including the following steps: A different metric from the maximum likelihood detection algorithm in the first step is used, and a secondary detection is performed on the symbol constellation combination in the candidate set based on this metric; also based on the maximum likelihood criterion, the calculated metric values ​​are sorted in ascending order, and the symbol constellation combination ranked first is the target decoding signal , the calculation expression is as follows:

[0026] in, Indicates the effective user channel; Represents the regularization factor, which is introduced to avoid the unsolvable problem caused by the rank-one precoding matrix.

[0027] In a second aspect, a two-step detection system based on a maximum likelihood criterion is provided, comprising: A preliminary decoding module is used to detect and sort all possible symbol constellation combinations through a maximum likelihood detection algorithm, and select the symbol constellation combination with the smallest distance value as the preliminary decoding result based on the maximum likelihood criterion to complete the first step of detection; A candidate set building module is used to set a detection threshold, and based on the distance value sorting obtained in the first detection step, find all other distance values ​​whose difference with the distance value corresponding to the preliminary decoding result is within the detection threshold range, and store the corresponding symbol constellation combination in the candidate set; The target decoding signal detection module is used to adopt a metric standard different from the maximum likelihood detection algorithm in the first step detection, and perform a second step detection on the symbol constellation combination in the candidate set based on the maximum likelihood criterion, and find the symbol constellation combination with the smallest metric value as the target decoding signal.

[0028] According to a third aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the two-step detection method based on the maximum likelihood criterion is implemented.

[0029] Compared with the prior art, the present invention has at least the following beneficial effects: The two-step detection method based on the maximum likelihood criterion of the present invention adds a re-detection step on the basis of the traditional maximum likelihood detection algorithm, with the purpose of improving the accuracy and reliability of decoding through secondary screening. The method of the present invention firstly performs preliminary detection and distance value sorting on all possible symbol constellation combinations based on the maximum likelihood criterion through the traditional maximum likelihood detection algorithm, and selects the symbol constellation combination with the smallest distance value as the preliminary decoding result. The first step of detection is to facilitate the subsequent second step detection by maximizing the similarity between the decoded signal and the transmitted signal. Subsequently, by setting a reasonable detection threshold, candidate signals similar to the preliminary decoding result are further screened out and placed in the candidate set. Finally, a metric different from the traditional maximum likelihood detection algorithm is used to perform secondary detection on the symbol constellation combination in the candidate set. Also based on the maximum likelihood criterion, the symbol constellation combination corresponding to the minimum metric value in the secondary detection is determined as the final decoding signal. The second step of detection is to maximize the decoding accuracy in the complex signal space under high-order modulation. The method of the present invention effectively solves the "error platform" problem faced by the MU-MIMO downlink system when using symbol-level transmission precoding based on interference utilization under high-order modulation, and has significant performance gain. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 FIG. 4 is a system block diagram of MU-MIMO according to an embodiment of the present invention.

[0032] Figure 2 This is a diagram of the interference utilization precoding principle based on "symbol scaling" under 16QAM modulation in an embodiment of the present invention.

[0033] Figure 3 The method of the embodiment of the present invention adopts 16QAM modulation mode. , , When different regularization factors Schematic diagram of bit error rate performance under values; FIG4 (a) shows an embodiment of the present invention using 16QAM modulation. , When different thresholds Schematic diagram of bit error rate changing with signal-to-noise ratio; FIG4 (b) shows an embodiment of the present invention using 16QAM modulation. , When the threshold is selected Schematic diagram of bit error rate changing with signal-to-noise ratio when ; FIG5 (a) shows an embodiment of the present invention using 16QAM modulation. , , , When different thresholds Schematic diagram of bit error rate changing with signal-to-noise ratio; FIG5( b ) shows an embodiment of the present invention using 16QAM modulation. , , , When the threshold is selected Schematic diagram of bit error rate changing with signal-to-noise ratio when ; FIG6 (a) shows an embodiment of the present invention using 16QAM modulation. , , When different thresholds Schematic diagram of bit error rate changing with signal-to-noise ratio; FIG6 (b) shows an embodiment of the present invention using 16QAM modulation. , , When the threshold is selected Schematic diagram of bit error rate changing with signal-to-noise ratio when ; FIG7 (a) shows an embodiment of the present invention using 16QAM modulation. , , Schematic diagram of the bit error rate changing with the signal-to-noise ratio under different thresholds δ; FIG7 (b) shows an embodiment of the present invention using 16QAM modulation. , , When the threshold is selected Schematic diagram of the bit error rate changing with the signal-to-noise ratio. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, ordinary technicians in this field can also obtain other embodiments without making creative work.

[0035] See also Figure 1The two-step detection method based on the maximum likelihood criterion in the embodiment of the present invention is applicable to a multi-stream MU-MIMO downlink system, which includes a system equipped with A base station with 1 transmitting antenna, and multi-antenna user terminals, each of which is equipped with receiving antennas and meet . The number of received data streams is recorded as , which satisfies , then the modulated input signal at the base station can be expressed as:

[0036] in, Indicates that it will be sent to the user symbolic data stream.

[0037] In the downlink transmission process of the MU-MIMO system, since the receiving end users are equipped with multiple receiving antennas, it is possible that the number of user receiving antennas is not equal to the number of received data streams. When the number of user receiving antennas is greater than the number of received data streams, the original channel cannot be used directly to complete the solution of the precoding matrix.

[0038] The two-step detection method based on the maximum likelihood criterion in the embodiment of the present invention mainly includes the following steps: All possible symbol constellation combinations are detected and sorted by the maximum likelihood detection algorithm, and based on the maximum likelihood criterion, the symbol constellation combination with the smallest distance value is selected as the preliminary decoding result to complete the first step of detection; Set a detection threshold, sort the distance values ​​obtained in the first detection step, find all other distance values ​​whose difference with the distance value corresponding to the preliminary decoding result is within the detection threshold, and store the corresponding symbol constellation combination in the candidate set; A metric different from the maximum likelihood detection algorithm in the first step is used, and the symbol constellation combination in the candidate set is detected in the second step based on the maximum likelihood criterion to find the symbol constellation combination with the smallest metric value as the target decoding signal.

[0039] In a possible implementation, the two-step detection method based on the maximum likelihood criterion of an embodiment of the present invention also includes applying singular value decomposition to the user's channel matrix to obtain an equivalent channel matrix, combining the equivalent channel matrices of all users to obtain an equivalent channel of the MU-MIMO system; and using the equivalent channel of the MU-MIMO system to calculate the symbol-level transmit precoding matrix.

[0040] Specifically, the embodiment of the present invention uses singular value decomposition to perform equivalent transformation of the original channel to obtain an equivalent low-dimensional MU-MIMO channel. The specific method is as follows: First, for users The channel matrix Using singular value decomposition, that is:

[0041] in, yes The singular value matrix of and are all unitary matrices.

[0042] Next, based on the number of received data streams of the user right Divide into blocks, and the dimensions are and The two sub-matrices of and ,Right now:

[0043] In fact, Corresponds to The submatrix composed of the largest singular value vectors of , which are the vectors most likely to be used to carry users The channel vector of the data symbol of interest. Therefore, we can use The user The equivalent channel matrix Constructed, expressed as:

[0044] All users Combined together, we get the equivalent channel of the entire system , at this time, the original MU-MIMO system is equivalent to a channel matrix low-dimensional MU-MIMO system, and then directly use the equivalent channel Calculate the symbol-level transmit precoding matrix.

[0045] In a possible implementation, the two-step detection method based on the maximum likelihood criterion of an embodiment of the present invention also includes constructing a symbol-level transmit precoding optimization problem based on interference utilization under the constraint of the total available transmit power of the base station through an equivalent channel of the MU-MIMO system, obtaining a symbol-level transmit precoding matrix by solving the symbol-level transmit precoding optimization problem based on interference utilization, and obtaining a precoded signal of the base station according to the symbol-level transmit precoding matrix.

[0046] For details, take 16QAM modulation as an example. Figure 2 , for the constellation point under consideration Decomposing along the direction of the detection threshold, we get:

[0047] Similarly, for User's The decoded signal stream is decomposed along the direction of the detection threshold, and the following is obtained:

[0048] in, as well as These are two new column vectors introduced in the 16QAM constellation; and are two detection thresholds parallel to each constellation point; and are two real scaling factors, indicating the severity of the interference on the decoded signal stream. users, the above formula can be expressed in a compact form, namely:

[0049] Specifically, the 16QAM constellation points are decomposed into two sets, where Indicates the constellation point that can be used for interference, that is, Figure 2 The real part of point "B", the imaginary part of point "C", and the real and imaginary parts of point "D"; the set Indicates the constellation point that cannot be used for interference, that is, Figure 2 The real part of point "C", the imaginary part of point "B", and the real and imaginary parts of point "A", etc. It can be obtained that under 16QAM modulation, if the noise-free decoded signal flow is to be located in the constructive area, that is, Figure 2 The green area in , then:

[0050] Furthermore, in the MU-MIMO downlink system, the MLD receiver operates independently at each user, and it only relies on its own channel matrix and precoding matrix during decoding, and cannot obtain information about other users.

[0051] Therefore, when designing a precoding matrix based on interference utilization, the only interference that the base station can utilize is the interference between data streams within the user, and the interference between users needs to be set to zero, that is, to satisfy:

[0052] According to the above derivation, when the base station preprocesses the transmitted signal through the symbol-level precoding SLP technology based on interference utilization, the optimization problem can be expressed as:

[0053] in, Indicates the total available transmit power of the base station.

[0054] Obviously, is a typical convex optimization problem and can be solved directly using convex optimization toolboxes such as CVX.

[0055] Furthermore, the symbol-level precoding SLP matrix is ​​obtained through the above optimization problem After that, the output signal after precoding processing at the base station can be obtained. ,Right now:

[0056] Based on the above settings, The received signal of a user It can be expressed as:

[0057] in, Indicates base station and user The channel matrix between Each term in follows a standard complex Gaussian distribution; The mean value at the receiving end is , the variance is Additive white Gaussian noise vector.

[0058] In a possible implementation, for At the receiving end, the two-step maximum likelihood detection (MLD) algorithm is used to detect the received signal. Decode to get the final demodulated signal .

[0059] Specifically, the first step of the detection operation is: Through the traditional maximum likelihood detection MLD algorithm, all The possible symbol constellation combinations are sorted by distance value, and based on the maximum likelihood criterion, the signal corresponding to the minimum distance value is selected As a preliminary decoding result, that is:

[0060] Specifically, the detection operation of the second step is: Set an appropriate detection threshold , for the distance values ​​obtained in the first step and sorted in ascending order, find the minimum difference between the distance values All other distance values ​​within the range are collected and stored in the candidate set. The symbol constellation combination corresponding to this set is the candidate signal that is close to the preliminary decoding result and is easy to confuse. (in ). On this basis, a metric different from the traditional maximum likelihood detection MLD algorithm is used, and the symbol constellation combinations in the candidate set are re-detected based on this metric. Also based on the maximum likelihood criterion, the calculated metric values ​​are sorted in ascending order. At this time, the symbol constellation combination ranked first is the final decoded signal ,Right now:

[0061] in, Indicates the effective user channel; Represents the regularization factor, which is introduced to avoid the unsolvable problem caused by the rank-one precoding matrix.

[0062] The advantages of the two-step detection method based on the maximum likelihood criterion of the present invention are further illustrated by simulation experiments below: Monte Carlo simulation is used to conduct simulation experiments on the proposed algorithm.

[0063] The test conditions are: In the downlink of the multi-stream MU-MIMO system, the base station is equipped with The transmitting antenna is There are multiple antenna users, where the user The number of receiving antennas is recorded as , the number of received data streams is recorded as Here the transmit power budget for each time slot is set to .

[0064] The simulation results are as follows Figure 3, Figure 4 (a), Figure 4 (b), Figure 5 (a), Figure 5 (b), Figure 6 (a), Figure 6 (b), Figure 7 (a) and Figure 7 (b), where "SLP+Traditional-MLD" means that symbol-level precoding is used at the transmitter to preprocess the transmitted signal, and the traditional MLD algorithm is used to decode the received signal at the receiver; "SLP+TwoSteps-MLD" means that symbol-level precoding is used at the transmitter to preprocess the transmitted signal, but the decoding operation at the receiver is performed through the two-step MLD algorithm; "BD+Traditional-MLD" means that traditional block diagonalization precoding is used at the transmitter to preprocess the transmitted signal, and the traditional MLD algorithm is used to decode the received signal at the receiver; "BD+TwoSteps-MLD" means that traditional block diagonalization precoding is used at the transmitter to preprocess the transmitted signal, but the decoding operation at the receiver is performed through the two-step MLD algorithm.

[0065] See also Figure 3 , Figure 3 The bit error rate (BER) performance of the proposed “SLP+TwoSteps-MLD” scheme under different regularization factor γ values ​​is shown. Here the simulation parameters are set to N T =16, The threshold is set to δ = 0.01. It is observed that the BER curves under different γ values ​​are almost overlapping, that is, the value of the regularization factor γ is not the main factor affecting the bit error rate BER performance, so the regularization factor of all subsequent simulations is selected as regularization factor γ = 1.

[0066] Please refer to Figures 4(a), 4(b) and 5(a), 5(b). Specifically, Figures 4(a), 4(b) and 5(a), 5(b) show the number of users. BER performance under different simulation parameter configurations. It can be observed from Figure 4(a) that when the threshold is set to When , the BER performance under all signal-to-noise ratios is better, so the fixed threshold is , thus obtaining the simulation result of Figure 4 (b). Similarly, the simulation result of Figure 5 (b) is also fixed at a threshold of It can be observed that for the symbol-level precoding SLP algorithm, the two-step MLD algorithm at the receiving end can effectively improve the "error platform" problem of the traditional MLD receiver under high signal-to-noise ratio. In particular, in these two simulation scenarios, the proposed "SLP+TwoSteps-MLD" scheme has obvious performance gains compared with other schemes. In addition, the difference between Figure 4 (a), Figure 4 (b) and Figure 5 (a), Figure 5 (b) lies in the number of user receiving antennas. In Figure 4 (a) and Figure 4 (b), the number of user receiving antennas is equal to the number of received data streams, while in Figure 5 (a) and Figure 5 (b), the number of user receiving antennas is greater than the number of received data streams. By comparison, when the number of antennas equipped by the user is more than the number of data streams, the system can use these additional antenna degrees of freedom to improve communication performance. Therefore, under the same signal-to-noise ratio conditions, Figure 5 (a) and Figure 5 (b) achieve a lower bit error rate BER than Figure 4 (a) and Figure 4 (b).

[0067] Please refer to Figures 6(a), 6(b) and 7(a), 7(b). Specifically, Figures 6(a), 6(b) and 7(a), 7(b) show the number of users. BER performance under different simulation parameter configurations. Similarly, according to Figure 6 (a) and Figure 7 (a) at different thresholds The performance comparison under these two simulation scenarios is fixed at the threshold . Similarly, it can be seen from both Figure 6 (b) and Figure 7 (b) that the "SLP+TwoSteps-MLD" scheme has the best bit error rate BER performance. In particular, for the scenario where the base station adopts the symbol-level precoding SLP algorithm, the proposed two-step maximum likelihood detection MLD algorithm can overcome the "error platform" problem of the traditional maximum likelihood detection MLD receiver to a great extent, especially under high signal-to-noise ratio, the improvement effect is more obvious. In addition, it can be observed that since the number of data streams in Figure 7 (a) and Figure 7 (b) is less than the number of receiving antennas, Figure 7 (a) and Figure 7 (b) have a lower bit error rate BER than Figure 6 (a) and Figure 6 (b) under the same signal-to-noise ratio.

[0068] Another embodiment of the present invention further provides a two-step detection system based on the maximum likelihood criterion, comprising: A preliminary decoding module is used to detect and sort all possible symbol constellation combinations through a maximum likelihood detection algorithm, and select the symbol constellation combination with the smallest distance value as the preliminary decoding result based on the maximum likelihood criterion to complete the first step of detection; A candidate set building module is used to set a detection threshold, and based on the distance value sorting obtained in the first detection step, find all other distance values ​​whose difference with the distance value corresponding to the preliminary decoding result is within the detection threshold range, and store the corresponding symbol constellation combination in the candidate set; The target decoding signal detection module is used to adopt a metric standard different from the maximum likelihood detection algorithm in the first step detection, and perform a second step detection on the symbol constellation combination in the candidate set based on the maximum likelihood criterion, and find the symbol constellation combination with the smallest metric value as the target decoding signal.

[0069] Another embodiment of the present invention further provides an electronic device, comprising: a memory storing at least one instruction; and a processor executing the instruction stored in the memory to implement the two-step detection method based on the maximum likelihood criterion.

[0070] Another embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the two-step detection method based on the maximum likelihood criterion is implemented.

[0071] Exemplarily, the instructions stored in the memory may be divided into one or more modules / units, which are stored in a computer-readable storage medium and executed by the processor to complete the two-step detection method based on the maximum likelihood criterion of the present invention. The one or more modules / units may be a series of computer-readable instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program in the server.

[0072] The electronic device may be a computing device such as a smart phone, a notebook, a PDA, and a cloud server. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the electronic device may also include more or fewer components, or a combination of certain components, or different components, for example, the electronic device may also include an input / output device, a network access device, a bus, etc.

[0073] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0074] The memory may be an internal storage unit of the server, such as a hard disk or memory of the server. The memory may also be an external storage device of the server, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card (FlashCard), etc. equipped on the server. Furthermore, the memory may include both an internal storage unit of the server and an external storage device. The memory is used to store the computer-readable instructions and other programs and data required by the server. The memory may also be used to temporarily store data that has been output or is to be output.

[0075] It should be noted that the information interaction, execution process and other contents between the above-mentioned module units are based on the same concept as the method embodiment. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0076] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0077] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the camera device / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0078] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0079] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A two-step detection method based on the maximum likelihood criterion, characterized in that: include: All possible symbol constellation combinations are detected and sorted by the maximum likelihood detection algorithm, and based on the maximum likelihood criterion, the symbol constellation combination with the smallest distance value is selected as the preliminary decoding result to complete the first step of detection; Set a detection threshold, sort the distance values ​​obtained in the first detection step, find all other distance values ​​whose difference with the distance value corresponding to the preliminary decoding result is within the detection threshold, and store the corresponding symbol constellation combination in the candidate set; A metric different from the maximum likelihood detection algorithm in the first step is used, and the symbol constellation combination in the candidate set is detected in the second step based on the maximum likelihood criterion to find the symbol constellation combination with the smallest metric value as the target decoding signal.

2. The two-step detection method based on the maximum likelihood criterion according to claim 1, characterized in that: A downlink system applicable to multi-stream MU-MIMO, the multi-stream MU-MIMO downlink system comprising a A base station with 1 transmitting antenna, and multi-antenna user terminals, each equipped with receiving antennas and meet ; The user The number of received data streams is recorded as ,satisfy , the modulated input signal at the base station is expressed as: in, Indicates that it will be sent to the user symbolic data stream; When the number of user receiving antennas is greater than the received data stream, the original channel cannot be used directly to solve the precoding matrix.

3. The two-step detection method based on the maximum likelihood criterion according to claim 2, characterized in that: It also includes applying singular value decomposition to the user's channel matrix to obtain an equivalent channel matrix, combining the equivalent channel matrices of all users to obtain the equivalent channel of the MU-MIMO system; and using the equivalent channel of the MU-MIMO system to calculate the symbol-level transmit precoding matrix.

4. The two-step detection method based on the maximum likelihood criterion according to claim 3 is characterized in that: The method of applying singular value decomposition to the channel matrix of the user to obtain an equivalent channel matrix, combining the equivalent channel matrices of all users, and obtaining the equivalent channel of the MU-MIMO system comprises the following steps: Press the button to the user The channel matrix Using singular value decomposition: in, yes The singular value matrix of and are all unitary matrices; User-based Number of received data streams right Divide into blocks, and the dimensions are and The two sub-matrices of and , the expression is as follows: In the above formula Corresponds to The submatrix composed of the largest singular value vector of The user The equivalent channel matrix Constructed, the expression is as follows: All users Combined to get the equivalent channel of the entire MU-MIMO system , at this time, the original MU-MIMO system is equivalent to a channel matrix Low-dimensional MU-MIMO system.

5. The two-step detection method based on the maximum likelihood criterion according to claim 4 is characterized in that: It also includes constructing a symbol-level transmit precoding optimization problem based on interference utilization under the constraint of total available transmit power of the base station through the equivalent channel of the MU-MIMO system, obtaining a symbol-level transmit precoding matrix by solving the symbol-level transmit precoding optimization problem based on interference utilization, and obtaining the precoded signal of the base station according to the symbol-level transmit precoding matrix.

6. The two-step detection method based on the maximum likelihood criterion according to claim 5, characterized in that: The method of constructing a symbol-level transmit precoding optimization problem based on interference utilization under the constraint of total available transmit power of a base station through an equivalent channel of a MU-MIMO system includes the following steps: For 16QAM modulation, for the constellation points considered Decomposing along the direction of the detection threshold, we get: For User's The decoded signal stream is decomposed along the direction of the detection threshold, and the following is obtained: In the formula, as well as These are two new column vectors introduced in the 16QAM constellation; and are two detection thresholds parallel to each constellation point; and are two real scaling factors, indicating the severity of the interference on the decoded signal stream; Users, the above formula is expressed in a compact form as follows: The 16QAM constellation points are decomposed into two sets, where Represents the constellation point that can be used for interference. If the noise-free decoded signal stream is located in the constructive area, the following expression is satisfied: When designing a precoding matrix based on interference utilization, the only interference that the base station can utilize is the interference between data streams within the user, and the interference between users is set to zero, that is, the following expression is satisfied: The symbol-level transmit precoding optimization problem based on interference utilization is expressed as follows: In the formula, Indicates the total available transmit power of the base station; The method of obtaining a symbol-level transmit precoding matrix by solving a symbol-level transmit precoding optimization problem based on interference utilization, and obtaining a precoded signal of a base station according to the symbol-level transmit precoding matrix comprises the following steps: The convex optimization toolbox is used to solve the symbol-level transmit precoding optimization problem based on interference utilization, and the symbol-level transmit precoding matrix is ​​obtained. , and obtain the output signal after precoding processing at the base station : Based on the above settings, The received signal of a user It is expressed as follows: In the formula, Indicates base station and user The channel matrix between Each term in follows a standard complex Gaussian distribution; The mean value at the receiving end is , the variance is Additive white Gaussian noise vector.

7. The two-step detection method based on the maximum likelihood criterion according to claim 6, characterized in that: The method of detecting and sorting all possible symbol constellation combinations by using the maximum likelihood detection algorithm and selecting the symbol constellation combination with the smallest distance value as the preliminary decoding result based on the maximum likelihood criterion, and completing the first step of detection includes the following steps: The maximum likelihood detection algorithm is used to detect all The possible symbol constellation combinations are sorted by distance value, and based on the maximum likelihood criterion, the signal corresponding to the minimum distance value is selected As a preliminary decoding result, the calculation expression is as follows: 。 8. The two-step detection method based on the maximum likelihood criterion according to claim 7, characterized in that: The method adopts a metric different from the maximum likelihood detection algorithm in the first step, and performs a second step detection on the symbol constellation combination in the candidate set based on the maximum likelihood criterion, and finds the symbol constellation combination with the smallest metric value as the target decoding signal, including the following steps: A different metric from the maximum likelihood detection algorithm in the first step is used, and a secondary detection is performed on the symbol constellation combinations in the candidate set based on this metric; also based on the maximum likelihood criterion, the calculated metric values ​​are sorted in ascending order, and the symbol constellation combination ranked first is the target decoding signal , the calculation expression is as follows: in, Indicates the effective user channel; Represents the regularization factor, which is introduced to avoid the unsolvable problem caused by the rank-one precoding matrix.

9. A two-step detection system based on the maximum likelihood criterion, characterized in that: include: A preliminary decoding module is used to detect and sort all possible symbol constellation combinations through a maximum likelihood detection algorithm, and select the symbol constellation combination with the smallest distance value as the preliminary decoding result based on the maximum likelihood criterion to complete the first step of detection; A candidate set building module is used to set a detection threshold, and based on the distance value sorting obtained in the first detection step, find all other distance values ​​whose difference with the distance value corresponding to the preliminary decoding result is within the detection threshold range, and store the corresponding symbol constellation combination in the candidate set; The target decoding signal detection module is used to adopt a metric standard different from the maximum likelihood detection algorithm in the first step detection, and perform a second step detection on the symbol constellation combination in the candidate set based on the maximum likelihood criterion, and find the symbol constellation combination with the smallest metric value as the target decoding signal.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the two-step detection method based on the maximum likelihood criterion as claimed in any one of claims 1 to 8 is implemented.

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