Signal detection method and device, electronic equipment, chip and storage medium

Abstract

The invention provides a signal detection method and device, electronic equipment, a chip and a storage medium, and the method comprises the steps: obtaining a receiving signal, a sending signal corresponding to the receiving signal being a multi-user multiple-input multiple-output signal sent by network equipment on a first time-frequency resource for a first terminal and a second terminal; performing minimum mean square error detection processing on the received signal to determine an estimated value of the transmitted signal; determining a modulation parameter corresponding to the second terminal according to the estimated value of the sending signal; and determining the bit likelihood ratio of the received signal according to the modulation parameter corresponding to the second terminal. According to the scheme provided by the invention, when the bit likelihood ratio of the signal is determined, the system calculation amount is reduced, the system performance is maintained, and the balance between the system performance and the complexity is obtained.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a signal detection method, device, electronic device, chip and storage medium. Background Art

[0002] In the Orthogonal Frequency Division Multiplexing (OFDM) communication system, multi-antenna technology, namely Multiple Input Multiplex Output (MIMO) technology, is introduced. MIMO technology can transmit multiple data streams on the same physical resource block (PRB). When multiple data streams belong to the user equipment, it is called single-user MIMO. If multiple data streams belong to different user equipments, it is called multi-user MIMO. For the detection of multi-user MIMO, there may be problems such as system performance and computational complexity. Summary of the invention

[0003] The present disclosure provides a signal detection method, device, electronic device, chip and storage medium, which can reduce the system calculation amount while maintaining performance in the process of determining the bit likelihood ratio of a signal, thereby achieving a balance between system performance and complexity.

[0004] The first aspect embodiment of the present disclosure proposes a signal detection method, which includes: acquiring a received signal, where the transmitted signal corresponding to the received signal is a multi-user multiple-input multiple-output signal sent by a network device to a first terminal and a second terminal on a first time-frequency resource; performing minimum mean square error detection processing on the received signal to determine an estimated value of the transmitted signal; determining a modulation parameter corresponding to the second terminal based on the estimated value of the transmitted signal; and determining a bit likelihood ratio of the received signal based on the modulation parameter corresponding to the second terminal.

[0005] In some embodiments of the present disclosure, minimum mean square error detection processing is performed on the received signal to determine the estimated value of the transmitted signal, including: for each of the N subcarriers in the first time-frequency resource, the minimum mean square error matrix is ​​determined according to the noise power, the channel matrix, and the unit matrix; based on the minimum mean square error matrix of each subcarrier and the received signal, the estimated value of the transmitted signal of the first terminal and / or the estimated value of the transmitted signal of the second terminal on each subcarrier is determined.

[0006] In some embodiments of the present disclosure, determining the modulation parameter corresponding to the second terminal based on the estimated value of the transmitted signal includes: determining multiple preset modulation parameters; determining the normalized average distance corresponding to each preset modulation parameter based on the estimated value of the transmitted signal; and determining the preset modulation parameter whose normalized average distance meets the preset conditions among the multiple preset modulation parameters as the modulation parameter corresponding to the second terminal.

[0007] In some embodiments of the present disclosure, determining the normalized average distance corresponding to each preset modulation parameter based on the estimated value of the transmitted signal includes: determining the normalized constellation point corresponding to each preset modulation parameter based on the estimated value of the transmitted signal of the second terminal of N subcarriers; for each preset modulation parameter, determining the distance between the estimated value of the transmitted signal of the second terminal of each subcarrier and the normalized constellation point; based on the distance, determining the normalized average distance corresponding to each preset modulation parameter.

[0008] In some embodiments of the present disclosure, determining the bit likelihood ratio of a received signal according to the modulation parameters corresponding to the second terminal includes: performing orthogonal QR decomposition on the channel matrix of the received signal to obtain an estimated value y~ of the received signal and an R matrix that meets the first condition; determining a path measurement value for each subcarrier based on the R matrix and the modulation parameters corresponding to the second terminal; and determining the bit likelihood ratio of the received signal based on the path measurement value.

[0009] In some embodiments of the present disclosure, based on the R matrix and the modulation parameters corresponding to the second terminal, determining the path metric value of each subcarrier includes: for each subcarrier, determining the signal modulation order M of the first terminal, and initializing M metric values ​​to infinity; determining the estimated value of the transmitted signal of the first terminal from the M candidate sets Based on the modulation parameters corresponding to the second terminal, the R matrix, and the estimated value of the received signal of the second terminal Said Determining an estimated value of a transmitted signal of a second terminal based on Estimated value of the received signal of the first terminal R matrix, determines the first parameter; based on Estimated value of the received signal of the second terminal R matrix, determine the second parameter; and determine the path metric value by summing the first parameter and the second parameter, wherein each subcarrier has M path metric values.

[0010] In some embodiments of the present disclosure, determining the bit likelihood ratio of a received signal based on a path metric value includes: determining, for each subcarrier, a first metric value and a second metric value among M path metric values, wherein the first metric value is a metric value when the bit value is 0, and the second metric value is a metric value when the bit value is 1; determining a first minimum value of the ratio of the first metric value to noise power and a second minimum value of the ratio of the second metric value to noise power; and determining the difference between the first minimum value and the second minimum value as the bit likelihood ratio.

[0011] The second aspect embodiment of the present disclosure proposes a signal detection device, which includes: an acquisition module, used to acquire a received signal, the transmitted signal corresponding to the received signal is a multi-user multiple-input multiple-output signal sent by a network device to a first terminal and a second terminal on a first time-frequency resource; a processing module, used to perform minimum mean square error detection processing on the received signal to determine an estimated value of the transmitted signal; a first determination module, used to determine a modulation parameter corresponding to the second terminal based on the estimated value of the transmitted signal; and a second determination module, used to determine a bit likelihood ratio of the received signal based on the modulation parameter corresponding to the second terminal.

[0012] The third aspect embodiment of the present disclosure proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in the first aspect embodiment of the present disclosure, or execute the method described in the second aspect embodiment of the present disclosure.

[0013] The fourth aspect embodiment of the present disclosure proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the method described in the first aspect embodiment of the present disclosure, or to execute the method described in the second aspect embodiment of the present disclosure.

[0014] The fifth aspect embodiment of the present disclosure proposes a chip, including at least one processor and a communication interface, the communication interface is used to receive signals input into the chip or signals output from the above chip, the processor communicates with the communication interface and implements any method in the first aspect embodiment of the present disclosure through logic circuits or execution code instructions, or executes the method described in the second aspect embodiment of the present disclosure.

[0015] In summary, the present disclosure proposes a signal detection method, device, electronic device, chip and storage medium, which obtains an estimated value of the transmitted signal by performing minimum mean square error detection processing on the received signal, and obtains the modulation parameter corresponding to the second terminal based on the estimated value. The bit likelihood ratio (log-likelihood ratio, LLR) of the received signal can be determined according to the modulation parameter, which can reduce the system calculation amount while maintaining performance, and achieve a balance between system performance and complexity.

[0016] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0018] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present disclosure;

[0019] Figure 2 A flow chart of a signal detection method provided by an embodiment of the present disclosure;

[0020] Figure 3 A flow chart of a signal detection method provided by an embodiment of the present disclosure;

[0021] Figure 4 A flow chart of a signal detection method provided by an embodiment of the present disclosure;

[0022] Figure 5 A flow chart of a signal detection method provided by an embodiment of the present disclosure;

[0023] Figure 6 An example diagram of the architecture of a signal detection method provided in an embodiment of the present disclosure;

[0024] Figure 7 A schematic diagram of the structure of a signal detection device provided in an embodiment of the present disclosure;

[0025] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure;

[0026] Fig. 9 A schematic diagram of the chip structure provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0028] In the OFDM communication system, multi-antenna technology, namely MIMO technology, is introduced. MIMO technology can transmit multiple data streams on the same time-frequency resources, which can greatly improve the system capacity and transmission reliability. For single-user MIMO detection, the commonly used methods are minimum mean-square-error (MMSE) detection technology and sphere decoding (SD) detection technology. The performance of SD detection technology can be close to the optimal performance, that is, the performance of the maximum likelihood algorithm (ML), and the complexity of SD detection technology is much lower than that of ML algorithm. Therefore, it is often used as a single-user MIMO detection technology. In practice, for single-user MIMO detection, a combination method is generally used, which first uses MMSE to estimate the optimal path, and then uses the SD method to search around the optimal path. However, in the multi-user MIMO scenario, this method will have some problems.

[0029] When using the SD method for detection, it is necessary to know two pieces of information: known channel estimation and modulation mode. In the multi-user MIMO scenario, when using the single-user MIMO detection method, due to the presence of two or more users being paired, at the user receiving end, although the channel information experienced by the user and the paired user can be obtained, the modulation mode of the paired user cannot be obtained. Due to the lack of modulation mode information of paired users, it is difficult to use the SD method to detect multi-user MIMO. The best performing SD method in the prior art cannot be directly applied to multi-user MIMO scenarios.

[0030] For multi-user MIMO detection, the Joint Maximum Likelihood (JML) demodulation algorithm can be used. This algorithm can achieve better performance, but because it needs to traverse the modulation mode, the total amount of calculation increases sharply, the complexity is high, and it is difficult to implement; other methods include first using the autocorrelation matrix to whiten the interference, and then using MMSE for detection, or first determining the modulation mode of the interference based on the power ratio, and then performing sphere decoding detection, etc., all of which will affect the performance and lead to poor performance.

[0031] In summary, in order to solve the technical problems in the related technology, the embodiment of the present disclosure provides a signal detection method, which obtains an estimated value of the transmitted signal by performing minimum mean square error detection processing on the received signal, and determines the modulation parameters corresponding to the second terminal based on the estimated value of the transmitted signal. According to the modulation parameters corresponding to the second terminal, the bit likelihood ratio of the received signal can be determined, thereby achieving the best balance between performance and complexity while reducing the amount of system calculation.

[0032] Before introducing the detailed solution of the present disclosure, the scenario to which the solution of the present disclosure is applied is described first. Figure 1 FIG. 1 is an application scenario diagram of a signal detection method in an embodiment. Figure 1 As shown, the disclosed solution can be applied in an OFDM communication system, a multi-user MIMO communication scenario, and a base station schedules two or more users simultaneously.

[0033] In the communication system, Multi-User Multiple Input Multiple Output (MU-MIMO) technology allows a base station (also called gNodeB) to transmit data to multiple user equipment (UE) simultaneously on the same time-frequency resources. These users to whom the base station transmits data simultaneously are called paired users. Figure 1 As shown, if UE1 and UE2 are paired, the base station can transmit data to the two UEs simultaneously on the same time-frequency resources through appropriate precoding. The base station precoding can make the channels experienced by the paired users as orthogonal as possible when they arrive at the UE side, so that the UE can use a simple linear method to separate and detect signals. In practical applications, due to factors such as the time-varying nature of the channel and the limited quantization of uplink feedback, the base station cannot guarantee the orthogonality of the paired user channels. Therefore, there is interference caused by the paired UE on the UE receiving side. The purpose of the disclosed solution for multi-user MIMO detection is to solve the optimal detection strategy in the case of interference caused by paired UEs.

[0034] Figure 2 A flow chart of a signal detection method provided by an embodiment of the present disclosure. Figure 2 As shown, the method can be executed by an electronic device, optionally, the method can be executed by a terminal or user equipment UE, optionally, the method can be executed by a signal receiving device. Optionally, a multi-user MIMO system allows a network device to transmit data to multiple UEs simultaneously on the same time-frequency resources. These UEs to which data is simultaneously transmitted by the base station are called paired UEs. The method can be executed by any of the paired UEs, wherein the UE executing the method is the desired UE and the other UEs are interfering UEs. The method can include the following steps.

[0035] Step 201, obtaining a received signal.

[0036] In some embodiments, the transmitted signal corresponding to the received signal is a multi-user multiple-input multiple-output signal sent by the network device to the first terminal and the second terminal on the first time-frequency resource.

[0037] In some embodiments, the name of the first terminal may be a signal receiving end, a desired user, UE2, etc. The first terminal may receive signals and detect signals.

[0038] In some embodiments, the second terminal may be an interfering user, UE1, etc., and the second terminal and the first terminal are paired users.

[0039] In some embodiments, the first terminal can receive a multi-user multiple-input multiple-output signal sent by a signal sending end on a first time-frequency resource, where the signal sending end can be a base station, such as a gNodeB base station.

[0040] Step 202: Perform minimum mean square error detection processing on the received signal.

[0041] In some embodiments, the first terminal may perform minimum mean square error detection processing on the received signal to determine an estimated value of the transmitted signal.

[0042] In some embodiments, the first terminal may determine the minimum mean square error matrix of each subcarrier based on the noise power, the channel matrix, and the unit matrix of each subcarrier in the N subcarriers in the first time-frequency resource.

[0043] In some embodiments, an estimated value of a signal transmitted by the first terminal and / or the second terminal for each subcarrier may be obtained based on a minimum mean square error matrix of each subcarrier and a received signal.

[0044] Step 203: Determine a modulation parameter corresponding to the second terminal according to the estimated value of the transmitted signal.

[0045] In some embodiments, multiple modulation parameters may be preset for blind detection of the modulation mode of the second terminal.

[0046] In some embodiments, for each preset modulation parameter, the normalized average distance of the corresponding constellation diagram may be calculated respectively.

[0047] In some embodiments, the normalized average distances corresponding to each preset modulation parameter may be compared to determine the modulation parameter corresponding to the smallest normalized average distance value as the modulation parameter corresponding to the second terminal.

[0048] Step 204: Determine a bit likelihood ratio of the received signal according to the modulation parameters corresponding to the second terminal.

[0049] In some embodiments, an orthogonal QR decomposition is performed on the received signal channel matrix to obtain an estimated value y~ of the received signal and an R matrix that meets a first condition, wherein the first condition may be an upper triangular matrix.

[0050] In some embodiments, a path metric value may be calculated for each subcarrier based on the R matrix and the modulation parameters corresponding to the second terminal.

[0051] In some embodiments, the difference between the two smallest values ​​of the plurality of path metric values ​​may be taken, and the difference may be determined as the bit likelihood ratio.

[0052] In some embodiments, determining the bit likelihood ratio of the received signal may use sphere decoding (Layered Orthogonal Lattice Detector, LORD) detection.

[0053] In summary, the above-mentioned embodiments of the present application, by performing minimum mean square error detection processing on the received signal, determining the estimated value of the transmitted signal, and presetting the modulation parameters for blind detection to obtain the modulation parameters corresponding to the second terminal, can reduce the amount of calculation, obtain the path measurement value based on the modulation parameters, and select the difference between the two smallest values, which is determined as the bit likelihood ratio of the received signal. This process can adopt LORD detection technology, which can achieve a balance between system performance and complexity.

[0054] Figure 3 A flow chart of a signal detection method provided by an embodiment of the present disclosure. Figure 3 As shown, based on Figure 2 In the embodiment shown, this embodiment specifically describes the above step 202. The method may include the following steps.

[0055] Step 301: for each of the N subcarriers in the first time-frequency resource, determine a minimum mean square error matrix according to noise power, a channel matrix, and a unit matrix.

[0056] In some embodiments, the first time-frequency resource may include N subcarriers, the first terminal may be a signal receiving end, and there are N r antenna, the minimum mean square error matrix of the i-th subcarrier can be calculated using the following formula:

[0057]

[0058] Wherein N0 may represent noise power, I represents a K*K-dimensional identity matrix, and K may represent the number of paired UEs on the same time-frequency resources.

[0059] YesN r ×K-dimensional channel matrix, where represents the channel vector of the jth UE, H i is the set of channel vectors of K UEs.

[0060] Step 302: Determine an estimated value of a transmitted signal of a first terminal and / or an estimated value of a transmitted signal of a second terminal on each subcarrier based on a minimum mean square error matrix of each subcarrier and a received signal.

[0061] In some embodiments, the frequency domain received signal model of the i-th subcarrier may be expressed by the following formula:

[0062] y i =H i x i +n i ,i=1,…,N

[0063] in: is the Nr-dimensional received signal column vector, which is the receiving end N r The set of frequency domain signal reception of Nr subcarriers corresponding to the root antenna.

[0064] It is a K-dimensional column vector, representing K UEs.

[0065] It is an Nr-dimensional column vector with a power of N0, representing a set of Nr noise vectors.

[0066] In some embodiments, paired users on the same time-frequency resource may include a first terminal and one or more second terminals. For example, when the number of paired users is 2, there is a first terminal and a second terminal. To represent the frequency domain received signal on the i-th subcarrier of the first terminal,

[0067] In some embodiments, the signal vector x is sent i Estimates MMSEEst(i) is MMSEEst(i). For example, when the number of paired users K=2, the estimation can be expressed by the following formula:

[0068]

[0069] The estimate The vector contains the first terminal estimate and the second terminal estimates Since the modulation mode corresponding to the second terminal needs to be detected, the estimation of the second terminal is required. Therefore, it can be determined

[0070] In some embodiments, if there is only one second terminal, the obtained If the number is N, and there are K-1 second terminals, we can get N·(K-1)

[0071] In summary, in the above embodiments of the present application, for each subcarrier, the minimum mean square error matrix can be obtained by calculating the formula according to its noise power, channel matrix, and unit matrix. Based on the minimum mean square error matrix and the received signal, the estimated value of the transmitted signal of the first terminal and / or the second terminal can be obtained, wherein the estimated value of the second terminal can facilitate the subsequent determination of the modulation mode corresponding to the second terminal.

[0072] Figure 4 A flow chart of a signal detection method provided by an embodiment of the present disclosure. Figure 4 As shown, based on Figure 2 In the embodiment shown, this embodiment specifically describes the above step 203. The method may include the following steps.

[0073] Step 401: determine a plurality of preset modulation parameters.

[0074] In some embodiments, the modulation parameters corresponding to the second terminal can be blindly detected by presetting a plurality of modulation parameters. For example, four modulation parameters, QPSK, 16QAM, 64QAM, and 256QAM, can be selected.

[0075] In some embodiments, multiple preset modulation parameters may be defined. For example, the following modScale[4] is defined when four preset modulation parameters are selected:

[0076]

[0077] InvertmodScale[4]={sqrt(2),sqrt(10),sqrt(42),sqrt(170)}

[0078] Wherein, sqrt(·) represents a square root operation, and InvertmodScale is the inverse value of modScale.

[0079] Step 402: Determine a normalized average distance corresponding to each preset modulation parameter according to the estimated value of the transmitted signal.

[0080] In some embodiments, the first terminal may determine a normalized constellation point corresponding to each preset modulation parameter based on an estimated value of a transmitted signal of the second terminal of N subcarriers.

[0081] In the above embodiment, after calculating the MMSEEst(i) of each subcarrier, the corresponding normalized constellation points xstd(i) and ystd(i) can be obtained, and the calculation process is as follows:

[0082] inIQ(i)=InvertmodScale[j]*MMSEEst(i),i=1,2,…,N

[0083]

[0084]

[0085] zx(i)=2·round(X(i))-1,i=1,2,…,N

[0086] zy(i)=2·round(Y(i))-1,i=1,2,…,N

[0087] xstd(i)=modScale[1]*zx(i),i=1,2,…,N

[0088] ystd(i)=modScale[1]*zy(i),i=1,2,…,N

[0089] Among them, real(·) means taking the real part of a complex number, imag(·) means taking the imaginary part of a complex number, round(·) means rounding operation, abs(·) means finding the absolute value operation, and min(·) means finding the minimum value.

[0090] In some embodiments, the first terminal may determine, for each preset modulation parameter, a distance between an estimated value of a transmitted signal of the second terminal and a normalized constellation point for each subcarrier.

[0091] In the above embodiment, the first terminal may calculate the distance absXerr(i) between all MMSEEst(i) estimation values ​​and the corresponding normalized constellation point xstd(i) and the distance absYerr(i) between ystd(i), and the calculation process is as follows:

[0092] Xerr(i)=real(MMSEEst(i))-xstd(i),i=1,2,…,N

[0093] Yerr(i)=imag(MMSEEst(i))-ystd(i),i=1,2,…,N

[0094] absXerr(i)=abs(Xerr(i)),i=1,2,…,N

[0095] absYerr(i)=abs(Yerr(i)),i=1,2,…,N

[0096] In some embodiments, based on the distance between the estimated value of the transmitted signal of the second terminal and the normalized constellation point, a normalized average distance corresponding to each preset modulation parameter may be determined.

[0097] In the above embodiment, for a certain preset modulation parameter, the corresponding normalized mean distance normDistance(j) may be calculated based on the distance meanDistance between the estimated value of the transmitted signal of the second terminal and the normalized constellation point, and the calculation process is as follows:

[0098]

[0099] normDistance(j)=meanDistance*InvertmodScale[j]

[0100] Step 403: Determine the preset modulation parameter whose normalized average distance meets the preset condition among the multiple preset modulation parameters as the modulation parameter corresponding to the second terminal.

[0101] In some embodiments, the preset modulation mode can be changed and step 402 can be repeated to obtain the normalized average distance corresponding to each preset modulation parameter. For example, when there are four preset modulation parameters, four normalized average distances can be obtained, which can be expressed as normDistance(j), j=1,...,4.

[0102] In some embodiments, an average value of multiple normalized average distances may be calculated, and a modulation parameter corresponding to a minimum value thereof may be determined as the modulation parameter corresponding to the second terminal.

[0103] In summary, the above-mentioned embodiments of the present application, by presetting multiple modulation parameters and calculating the corresponding normalized average distance for each modulation parameter, determine the modulation parameter corresponding to the minimum average distance, which is the modulation parameter corresponding to the second terminal, and realize blind detection of the modulation parameter of the second terminal based on the mean square error matrix. The blind detection only uses the estimated value of MMSE. The MIMO detection of the received signal is performed after the modulation mode is detected. Therefore, its calculation amount is much smaller than that of the JML algorithm, which can reduce the calculation amount of the system and reduce the complexity.

[0104] Figure 5 A flow chart of a signal detection method provided by an embodiment of the present disclosure. Figure 5 As shown, based on Figure 1 In the embodiment shown, this embodiment specifically describes the above step 204. The method may include the following steps.

[0105] Step 501: perform orthogonal QR decomposition on the channel matrix of the received signal to obtain an estimated value y~ of the received signal and an R matrix that meets the first condition.

[0106] In some embodiments, H i Perform orthogonal QR decomposition and then multiply by Q H , we can get the estimated value of the received signal And the R matrix that meets the first condition, taking the case of only one second terminal as an example, for the i-th subcarrier, the received signal y i The expression is right Perform orthogonal QR decomposition and then multiply by the conjugate transposed matrix Q of the unit orthogonal matrix H ,get The results are as follows:

[0107]

[0108] Among them, R is a matrix that meets the first condition, that is, an upper triangular matrix This matrix can realize R·x i Only relevant to the first terminal; YesN r ×K-dimensional channel matrix, where: represents the channel vector of the jth UE, whose dimension is N r ; is a K-dimensional column vector, representing K UEs; YesN r dimensional noise column vector, whose power is N0.

[0109] Step 502: Determine a path metric value of each subcarrier based on the R matrix and a modulation parameter corresponding to the second terminal.

[0110] In some embodiments, for each subcarrier, a signal modulation order M of the first terminal may be determined, and M metric values ​​may be initialized to infinity.

[0111] In the above embodiment, the modulation order M is M paths of a subcarrier. When the transmission contents of the M paths are unclear, the metric values ​​corresponding to the M paths may be initialized to infinity.

[0112] In some embodiments, the estimated value of the transmitted signal of the first terminal may be determined from the M candidate sets.

[0113] In the above embodiment, the first As the estimated value of the transmitted signal of the first terminal And perform the operation, then select the second Repeat this step until M candidates are found. All operations are completed.

[0114] In some embodiments, based on the modulation parameters corresponding to the second terminal, the R matrix, and the estimated value of the received signal of the second terminal Determining an estimated value of a transmitted signal of a second terminal

[0115] In the above embodiment, the estimated value of the transmitted signal of the second terminal can be obtained by the following operation:

[0116]

[0117] In some embodiments, based on Estimated value of the received signal of the first terminal R matrix, determines the first parameter.

[0118] In the above embodiment, the expression of the first parameter is in is an estimated value of a received signal of the first terminal.

[0119] In some embodiments, based on Estimated value of the received signal of the second terminal R matrix, determines the second parameter.

[0120] In the above embodiment, the second parameter expression is: in is an estimated value of the received signal of the second terminal.

[0121] In some embodiments, the path metric value is determined by summing the first parameter and the second parameter, wherein each subcarrier has M path metric values.

[0122] In the above embodiment, the path metric value is the sum of the first parameter and the second parameter, which can be expressed as follows:

[0123]

[0124] We can calculate the corresponding path metrics for each of the M paths and obtain M

[0125] Step 503: Determine a bit likelihood ratio of the received signal based on the path metric value.

[0126] In some embodiments, for each subcarrier, a first metric value and a second metric value among the M path metric values ​​may be determined, wherein the first metric value is a metric value when the bit value is 0, and the second metric value is a metric value when the bit value is 1.

[0127] In some embodiments, a first minimum value of the ratio of the first metric value to the noise power and a second minimum value of the ratio of the second metric value to the noise power are determined.

[0128] In the above embodiment, the first minimum value expression of the ratio of the first metric value to the noise power is: The second minimum expression of the ratio of the second metric value to the noise power is minxi:bks=11N0y-R·xi2.

[0129] In some embodiments, the difference between the first minimum value and the second minimum value is determined as a bit likelihood ratio.

[0130] In the above embodiment, the first minimum value and the second minimum value can be subjected to a difference process to obtain a difference value, and the difference value is determined to be a bit likelihood ratio, that is, LLR (b k ), its operation expression is as follows:

[0131]

[0132] In summary, the above-mentioned embodiments of the present application perform orthogonal QR decomposition on the received signal to obtain the received signal estimation value y~ and the R matrix that meets the first condition. Based on the R matrix and the modulation parameters corresponding to the second terminal, the path measurement value of each subcarrier can be determined. According to the path measurement value, the bit likelihood ratio of the received signal can be obtained, and the LORD detection is used to detect multi-user MIMO, thereby maintaining the system performance and achieving a balance between performance and complexity.

[0133] For the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present disclosure is not limited by the described order of actions, because according to the present disclosure, certain steps can be performed in other orders or simultaneously.

[0134] Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present disclosure.

[0135] The technical solution of the present disclosure is further described in detail below in conjunction with specific application examples.

[0136] Figure 6 An example diagram of a signal detection architecture provided in an embodiment of the present disclosure is shown. The number of paired UEs in the example architecture is 2, namely UE1 and UE2, where UE1 is an interfering user and UE2 is a desired user.

[0137] The architecture includes one or more mean square error detection processing modules, a modulation mode blind detection module, a LORD detection module and a delay module.

[0138] In the mean square error detection processing module, the MMSE algorithm is used to obtain the symbol estimation of the paired interfering users on multiple subcarriers. First, we can get the minimum mean square error matrix Its formula is

[0139]

[0140] Based on this matrix, the transmitted signal vector x can be obtained i The estimated x i is: MMSEEst(i)

[0141]

[0142] Wherein N0 may represent noise power, I represents a K*K-dimensional identity matrix, and K may represent the number of paired UEs on the same time-frequency resources.

[0143] YesN r ×K-dimensional channel matrix, where represents the channel vector of the jth UE, H i is the set of channel vectors of K UEs.

[0144] This estimate The vector includes the expected user and disturbing users In order to detect the interference modulation mode below, only the estimated value of the interference is needed remember i=1,…,N. For multiple mean square error detection modules, the value of MMSEEst(i) is calculated.

[0145] In the modulation mode blind detection module, four modulation modes can be assumed respectively, and the symbol estimates are normalized under this assumption to obtain four normalized distances. The specific operation is as follows.

[0146] Assume that N interference estimates are obtained from MMSE equalization, expressed as: MMSEEst(i), i = 1, 2, ..., N. And define 4 modulation parameters as:

[0147]

[0148] InvertmodScale[4]={sqrt(2),sqrt(10),sqrt(42),sqrt(170)}

[0149] Calculate the normalized average distance of the constellation diagram of the four modulation modes. For the jth modulation mode, the steps are:

[0150] The corresponding normalized constellation points xstd(i) and ystd(i) are obtained from the input MMSEEst(i) through the following series of calculations.

[0151] Calculate the distances between all MMSEEst(i) estimates and the corresponding normalized constellation points xstd(i) and ystd(i).

[0152] Calculate the normalized average distance of its constellation diagram.

[0153] By changing the value of j and repeating the first to third steps above, the normalized average distance normDistance(j) of the constellation diagram can be obtained, where j = 1,…,4.

[0154] For normDistance(j), j=1,…,4, find the minimum value. The subscript corresponding to the minimum value is the interference modulation mode ModLevel.

[0155] The LORD detection module can use the LORD algorithm to demodulate and obtain LLR when the desired user and the interfering user are known, assuming that the modulation order of the desired UE signal is M2. The steps include:

[0156] Initialize M2 metrics to infinity.

[0157] Select the first one from M2 candidate sets Calculated The value of .

[0158] In the known In the case of, calculate according to the following expression

[0159]

[0160] Bundle Substitution You can get the value of the second item.

[0161] Finally, all path metrics can be obtained

[0162] The calculation formula for the k-th bit soft information LLR of the signal layer is:

[0163]

[0164] The delay module can be used to wait for the mean square error detection processing module to complete processing.

[0165] In summary, the mean square error detection processing module of this example processes the received signal to obtain an estimated value of interference The modulation mode blind detection module can obtain the modulation mode of interference based on the estimated value, reduce the system calculation amount and reduce the complexity. The LORD detection module can calculate the path metric value to obtain LLR, which can maintain good system performance and achieve the best balance between performance and complexity.

[0166] Figure 7 700 is a block diagram of a signal detection device 700 provided in an embodiment of the present disclosure. Figure 7 As shown, the device 700 includes:

[0167] The acquisition module 710 is used to acquire a received signal, where the transmission signal corresponding to the received signal is a multi-user multiple-input multiple-output signal sent by the network device to the first terminal and the second terminal on the first time-frequency resource; the processing module 720 is used to perform minimum mean square error detection processing on the received signal to determine an estimated value of the transmission signal; the first determination module 730 is used to determine the modulation parameter corresponding to the second terminal based on the estimated value of the transmission signal; the second determination module 740 is used to determine the bit likelihood ratio of the received signal based on the modulation parameter corresponding to the second terminal.

[0168] In summary, the device 700 obtains the received signal through the acquisition module, and the processing module performs minimum mean square error detection processing on the obtained received signal to obtain an estimated value of the transmitted signal. The first determination module can determine the modulation parameter corresponding to the second terminal through blind detection based on the estimated value of the transmitted signal, thereby reducing the system complexity. The second determination module can obtain the bit likelihood ratio of the received signal through LORD detection based on the modulation parameter, thereby maintaining good system performance and achieving the best balance between complexity and performance.

[0169] In some embodiments, the processing module 720 is also used to perform: for each of the N subcarriers in the first time-frequency resource, determine the minimum mean square error matrix according to the noise power, the channel matrix, and the unit matrix; based on the minimum mean square error matrix of each subcarrier and the received signal, determine the estimated value of the transmitted signal of the first terminal and / or the estimated value of the transmitted signal of the second terminal on each subcarrier.

[0170] In some embodiments, the first determination module 730 is also used to execute: determining multiple preset modulation parameters; determining the normalized average distance corresponding to each preset modulation parameter based on the estimated value of the transmitted signal; and determining the preset modulation parameter whose normalized average distance among the multiple preset modulation parameters meets the preset conditions as the modulation parameter corresponding to the second terminal.

[0171] In some embodiments, the first determination module 730 is also used to perform: determining the normalized constellation point corresponding to each preset modulation parameter based on the estimated value of the transmitted signal of the second terminal of N subcarriers; for each preset modulation parameter, determining the distance between the estimated value of the transmitted signal of the second terminal of each subcarrier and the normalized constellation point; based on the distance, determining the normalized average distance corresponding to each preset modulation parameter.

[0172] In some embodiments, the second determination module 740 is used to perform: performing orthogonal QR decomposition on the channel matrix of the received signal to obtain an estimated value of the received signal and an R matrix that meets the first condition; determining a path metric value of each subcarrier based on the R matrix and a modulation parameter corresponding to the second terminal; and determining a bit likelihood ratio of a received signal based on the path metric value.

[0173] In some embodiments, the second determination module 740 is further configured to: determine, for each subcarrier, a signal modulation order M of the first terminal, and initialize M metric values ​​to infinity; determine an estimated value of the transmitted signal of the first terminal from the M candidate sets; Based on the modulation parameters corresponding to the second terminal, the R matrix, and the estimated value of the received signal of the second terminal Determining an estimated value of a transmitted signal of a second terminal based on Estimated value of the received signal of the first terminal R matrix, determines the first parameter; based on Estimated value of the received signal of the second terminal R matrix, determine the second parameter; and determine the path metric value by summing the first parameter and the second parameter, wherein each subcarrier has M path metric values.

[0174] In some embodiments, the second determination module 740 is also used to perform: for each subcarrier, determine the first metric value and the second metric value among the M path metric values, wherein the first metric value is the metric value when the bit value is 0, and the second metric value is the metric value when the bit value is 1; determine a first minimum value of the ratio of the first metric value to the noise power, and a second minimum value of the ratio of the second metric value to the noise power; and determine the difference between the first minimum value and the second minimum value as the bit likelihood ratio.

[0175] In summary, the device 700 determines multiple second QPs based on multiple first QPs, determines the target QP based on the multiple second QPs, and performs hierarchical processing on the QP. On the premise of obtaining the most appropriate QP value, the number of traversals is reduced, and system power consumption, bandwidth and storage are saved.

[0176] Figure 8A block diagram of an electronic device 800 for implementing the above-mentioned method for determining image coding parameters provided in an embodiment of the present disclosure.

[0177] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiment of the present disclosure, the embodiment of the present disclosure also provides an electronic device, such as Figure 8 As shown, the electronic device 800 includes:

[0178] Communication interface 801, capable of exchanging information with other devices;

[0179] The processor 802 is connected to the communication interface 801 to implement information interaction with other devices, and is used to execute the method provided by one or more of the above technical solutions when running the computer program;

[0180] A memory 803 , on which the computer program is stored.

[0181] Specifically, the processor 802 can be used to obtain multiple candidate quantization parameters QP according to the bit width of the image to be processed; obtain multiple first code streams based on multiple first QPs among the multiple candidate QPs; determine multiple second QPs based on the multiple first code streams and obtain multiple second code streams; determine a target QP based on the multiple second code streams, and the target QP is used to perform image compression processing on the image to be processed.

[0182] It should be noted that the specific processing process of the processor 802 can be understood by referring to the above method.

[0183] Of course, in actual application, the various components in the electronic device 800 are coupled together through the bus system 804. It can be understood that the bus system 804 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 804 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 8 Various buses are labeled as bus system 804 .

[0184] The memory 803 in the embodiment of the present application is used to store various types of data to support the operation of the electronic device 800. Examples of such data include: any computer program used to operate on the electronic device 800.

[0185] The method disclosed in the above embodiment of the present application can be applied to the processor 802, or implemented by the processor 802. The processor 802 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 802. The above-mentioned first processor 802 can be a general-purpose processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 802 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in the memory 803, and the processor 802 reads the information in the memory 803 and completes the steps of the above method in combination with its hardware.

[0186] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0187] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the above instructions can be executed by the processor 820 of the electronic device 800 to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0188] The embodiments of the present disclosure further provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the method for determining image coding parameters described in the above embodiments of the present disclosure.

[0189] Fig. 9 FIG. 1 is a schematic diagram of a structure of a chip 900 for implementing the above communication control method according to an exemplary embodiment. Fig. 9The chip 900 includes a communication interface 901 and at least one processor 902. The communication interface 901 is used to receive a signal input to the chip 900 or a signal output from the chip 900. The processor 902 communicates with the communication interface 901 and implements the communication control method described in the above embodiment of the present disclosure through a logic circuit or executing code instructions. It should be noted that for ease of description, only parts related to the relevant invention are shown in the drawings. The embodiments in this application and the features in the embodiments may be combined with each other without conflict.

[0190] It should be understood that the "system", "device", "unit" and / or "module" used in this application is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the word can be replaced by other expressions.

[0191] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements. The elements defined by the sentence "includes a..." do not exclude the existence of other identical elements in the process, method, commodity or device that includes the elements.

[0192] In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0193] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0194] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0195] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0196] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0197] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (control method), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0198] It should be understood that the various parts of the embodiments of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0199] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0200] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent commodity, it may also be stored in a computer-readable storage medium. The above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0201] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A signal detection method, characterized in that: The method is performed by a first terminal, and includes: Acquire a received signal, where a transmitted signal corresponding to the received signal is a multi-user multiple-input multiple-output signal sent by a network device to the first terminal and the second terminal on a first time-frequency resource; Performing minimum mean square error detection processing on the received signal to determine an estimated value of the transmitted signal; Determining a modulation parameter corresponding to the second terminal according to the estimated value of the transmitted signal; Determine a bit likelihood ratio of the received signal according to a modulation parameter corresponding to the second terminal.

2. The method according to claim 1, characterized in that The performing minimum mean square error detection processing on the received signal to determine the estimated value of the transmitted signal includes: For each subcarrier of the N subcarriers in the first time-frequency resource, determine a minimum mean square error matrix according to noise power, a channel matrix, and a unit matrix; Based on the minimum mean square error matrix of each subcarrier and the received signal, an estimated value of the transmitted signal of the first terminal and / or an estimated value of the transmitted signal of the second terminal on each subcarrier is determined.

3. The method according to claim 2, characterized in that The determining, according to the estimated value of the transmitted signal, a modulation parameter corresponding to the second terminal includes: determining a plurality of preset modulation parameters; Determining a normalized average distance corresponding to each preset modulation parameter according to the estimated value of the transmitted signal; The preset modulation parameters whose normalized average distances meet preset conditions among the multiple preset modulation parameters are determined as the modulation parameters corresponding to the second terminal.

4. The method according to claim 3, characterized in that: Determining the normalized average distance corresponding to each preset modulation parameter according to the estimated value of the transmitted signal includes: Determining a normalized constellation point corresponding to each preset modulation parameter according to an estimated value of a transmitted signal of the second terminal of the N subcarriers; For each preset modulation parameter, determining a distance between an estimated value of a transmitted signal of the second terminal of each subcarrier and the normalized constellation point; Based on the distance, a normalized average distance corresponding to each preset modulation parameter is determined.

5. The method according to any one of claims 2 to 4, characterized in that: The determining, according to the modulation parameter corresponding to the second terminal, a bit likelihood ratio of the received signal includes: Performing orthogonal QR decomposition on the channel matrix of the received signal to obtain an estimated value of the received signal And the R matrix that meets the first condition; Determine a path metric value for each subcarrier based on the R matrix and a modulation parameter corresponding to the second terminal; Based on the path metric value, a bit likelihood ratio of the received signal is determined.

6. The method according to claim 5, characterized in that The determining, based on the R matrix and the modulation parameter corresponding to the second terminal, a path metric value of each subcarrier includes: For each subcarrier, determine a signal modulation order M of the first terminal, and initialize M metric values ​​to infinity; Determine an estimated value of the transmitted signal of the first terminal from the M candidate sets Based on the modulation parameter corresponding to the second terminal, the R matrix, and the estimated value of the received signal of the second terminal Said Determining an estimated value of a transmitted signal of the second terminal Based on the An estimated value of a received signal of the first terminal The R matrix determines the first parameter; Based on the The estimated value of the received signal of the second terminal Said The R matrix determines the second parameter; The path metric value is determined by summing the first parameter and the second parameter, wherein each subcarrier has M path metric values.

7. The method according to claim 6, characterized in that The determining, based on the path metric value, a bit likelihood ratio of the received signal comprises: For each subcarrier, determine a first metric value and a second metric value among the M path metric values, wherein the first metric value is a metric value when the bit value is 0, and the second metric value is a metric value when the bit value is 1; Determine a first minimum value of a ratio of the first metric value to the noise power and a second minimum value of a ratio of the second metric value to the noise power; A difference between the first minimum value and the second minimum value is determined as the bit likelihood ratio.

8. A signal detection device, characterized in that: The device comprises: An acquisition module, configured to acquire a received signal, wherein a transmitted signal corresponding to the received signal is a multi-user multiple-input multiple-output signal sent by a network device to the first terminal and the second terminal on a first time-frequency resource; A processing module, configured to perform minimum mean square error detection processing on the received signal to determine an estimated value of the transmitted signal; A first determining module, configured to determine a modulation parameter corresponding to the second terminal according to an estimated value of the transmitted signal; The second determination module is used to determine the bit likelihood ratio of the received signal according to the modulation parameter corresponding to the second terminal.

9. An electronic device, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 7.

11. A chip, characterized in that: It includes at least one processor and a communication interface; the communication interface is used to receive a signal input to the chip or a signal output from the chip, and the processor communicates with the communication interface and implements the method as described in any one of claims 1 to 7 through a logic circuit or executing code instructions.

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