Signal demodulation method and device, baseband chip, terminal equipment and storage medium

Abstract

Embodiments of the application disclose a signal demodulation method and device, a baseband chip, a terminal device and a storage medium, and belong to the technical field of communication. The method comprises: performing channel estimation and noise estimation on a received signal to obtain a channel matrix and an initial noise matrix; determining a noise matrix adjustment factor based on the channel matrix; adjusting the initial noise matrix based on the noise matrix adjustment factor to obtain a target noise matrix; and performing signal demodulation on the received signal by a target demodulation algorithm based on the channel matrix and the target noise matrix to obtain a signal demodulation result. In the process of determining the noise matrix adjustment factor, the baseband chip selects the channel matrix as the adjustment basis, which can realize corresponding change of the noise matrix adjustment factor under different channel environments, thereby enhancing the stability of matrix inversion in the target demodulation algorithm, and further improving the signal demodulation performance and demodulation quality.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of communication, in particular to a signal demodulation method and device, a baseband chip, a terminal device and a storage medium. BACKGROUND

[0002] In a wireless communication system, a terminal needs to demodulate a received signal by a signal demodulation algorithm to obtain the information modulated in the received signal.

[0003] In the signal demodulation process, the stability of the signal demodulation algorithm will directly affect the demodulation performance and quality. SUMMARY

[0004] Embodiments of the present application provide a signal demodulation method, device, baseband chip, terminal device and storage medium. The technical solution is as follows:

[0005] In one aspect, the present application provides a signal demodulation method, comprising:

[0006] channel estimation and noise estimation on a received signal to obtain a channel matrix and an initial noise matrix;

[0007] determining a noise matrix adjustment factor based on the channel matrix;

[0008] adjusting the initial noise matrix based on the noise matrix adjustment factor to obtain a target noise matrix;

[0009] demodulating the received signal by a target demodulation algorithm based on the channel matrix and the target noise matrix to obtain a signal demodulation result, the target demodulation algorithm involving a matrix inversion operation on a target matrix, the target matrix being determined based on the channel matrix and the target noise matrix.

[0010] In another aspect, the present application provides a signal demodulation device, comprising:

[0011] an estimation module configured to perform channel estimation and noise estimation on a received signal to obtain a channel matrix and an initial noise matrix;

[0012] an adjustment module configured to determine a noise matrix adjustment factor based on the channel matrix;

[0013] The adjustment module is further configured to adjust the initial noise matrix based on the noise matrix adjustment factor to obtain a target noise matrix.

[0014] demodulation module, configured to perform signal demodulation on the received signal based on the channel matrix and the target noise matrix by a target demodulation algorithm, to obtain a signal demodulation result, the target demodulation algorithm involving a matrix inversion operation on a target matrix, the target matrix being determined based on the channel matrix and the target noise matrix.

[0015] In another aspect, an embodiment of the present application provides a baseband chip, which comprises a programmable logic circuit and / or program instructions, and is configured to implement the signal demodulation method according to the above aspect when the baseband chip is running.

[0016] In another aspect, an embodiment of the present application provides a terminal device, which is provided with the baseband chip according to the above aspect.

[0017] In another aspect, an embodiment of the present application provides a computer readable storage medium, which stores at least one program, and the at least one program is configured to be executed by a processor to implement the signal demodulation method according to the above aspect.

[0018] In another aspect, an embodiment of the present application provides a computer program product, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to make the computer device perform the signal demodulation method according to the above aspect.

[0019] In the embodiment of the present application, the baseband chip performs channel estimation and noise estimation on the received signal to obtain a channel matrix and an initial noise matrix, and determines a noise matrix adjustment factor according to the channel matrix, adjusts the initial noise matrix by the noise matrix adjustment factor to obtain a target noise matrix, and then performs signal demodulation on the received signal by a target demodulation algorithm according to the channel matrix and the target noise matrix. In the process of determining the noise matrix adjustment factor, the baseband chip takes the channel matrix as the adjustment basis, can dynamically change the noise matrix adjustment factor in different channel environments, thereby enhancing the stability of the matrix inversion in the target demodulation algorithm, and further improving the signal demodulation performance and the demodulation quality. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 FIG. 1 is a schematic diagram of a system architecture according to an example embodiment of the present application;

[0021] Figure 2 FIG. 2 is a flow chart of a signal demodulation method according to an example embodiment of the present application;

[0022] Figure 3 FIG. 3 is a flow chart of a signal demodulation method according to another example embodiment of the present application;

[0023] Figure 4 This is a schematic diagram illustrating an exemplary embodiment of the signal demodulation process of this application;

[0024] Figure 5 This is a structural block diagram of a signal demodulation apparatus provided in an exemplary embodiment of this application;

[0025] Figure 6 This is a structural block diagram of a terminal device illustrated in an exemplary embodiment of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0027] In this article, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0028] In communication systems, signal transmission typically involves modulation and demodulation. Demodulation algorithms can be used to reconstruct the original signal at the receiving end of the communication system. Most demodulation algorithms utilize matrix operations.

[0029] The following example illustrates the demodulation algorithm using the Minimum Mean Squared Error (MMSE) theory applied to a Multiple Input Multiple Output (MIMO) system.

[0030] Schematic, a typical model of a MIMO system is y = Hx + n, where y represents a length of N. Rx The received signal column vector, N Rx Indicates the number of receiving antennas; H indicates a size of N. Rx *N Tx The channel matrix; x represents a channel matrix of length N. Tx The column vector of transmitted signals, N Tx This indicates the number of transmitting antennas; n represents the length N. Rx The noise column vector.

[0031] The MMSE-based demodulation scheme can be represented as:

[0032]

[0033] where A = HH H , nn = E{nn H} denotes the correlation matrix of the noise vector.

[0034] In the case that there is no correlation between the elements of n, the baseband chip usually performs noise whitening on the received signal, i.e. diagonalizes the correlation matrix of the noise vector, and simplifies to nn = σ 2 I, where σ 2 is the noise power possessed by a single antenna.

[0035] When N Rx < N Tx , the matrix A is an N Rx *N Rx semi-definite matrix, and when N Rx > N Tx , the demodulation scheme is deformed to obtain:

[0036]

[0037] where B = H H H, and the matrix B is an N Tx *N Tx semi-definite matrix. Through deformation of the demodulation scheme, the complexity of matrix inversion can be effectively reduced when N Rx > N Tx .

[0038] However, according to the properties of matrix inversion, the above demodulation scheme has instability in the case that the semi-definite matrix A or B is close to singular and the signal-to-noise ratio is high.

[0039] In order to improve the above demodulation scheme, in the related art, the diagonal elements of the correlation matrix R nn of the noise vector are adjusted to enhance the stability of the matrix inversion process. The adjustment method is generally to amplify the diagonal elements or add a small value to the diagonal elements, and the demodulation scheme after adjustment is:

[0040]

[0041]

[0042] where α > 1 is a multiplicative amplification factor; Δ > 0 is an additive increment factor. Since α and Δ are noise matrix adjustment factors, they are empirical values generated according to actual application and are fixed values, so in the case of high signal-to-noise ratio, the noise power σ 2The small value itself cannot be adjusted to the noise matrix effectively even if it is amplified or increased, so that the stability of matrix inversion cannot be improved.

[0043] In the embodiment of the application, the baseband chip obtains a channel matrix and an initial noise matrix by performing channel estimation and noise estimation on the received signal, determines a noise matrix adjustment factor according to the channel matrix, adjusts the initial noise matrix according to the noise matrix adjustment factor to obtain a target noise matrix, and then performs signal demodulation on the received signal according to the channel matrix and the target noise matrix through a target demodulation algorithm. In the process of determining the noise matrix adjustment factor, the baseband chip takes the channel matrix as the adjustment basis, can dynamically change the noise matrix adjustment factor in different channel environments, thereby enhancing the stability of matrix inversion in the target demodulation algorithm, and further improving the signal demodulation performance and demodulation quality.

[0044] Please refer to Figure 1 which shows a schematic diagram of a system architecture provided by an example embodiment of the application. The system architecture can include a terminal device 10 and a network device 20.

[0045] The number of terminal devices 10 is usually multiple, and one or more terminal devices 10 can be distributed in a cell managed by each network device 20. The terminal device 10 can include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem with wireless communication function, and various forms of user equipment (User Equipment, UE), mobile stations (Mobile Station, MS), etc. For convenience of description, the above-mentioned devices are collectively referred to as terminal devices in the embodiments of the application.

[0046] The network device 20 is a device deployed in an access network to provide wireless communication function for the terminal device 10. The network device 20 can include various forms of macro base stations, micro base stations, relay stations, access points, etc. In systems using different wireless access technologies, the names of devices with network device functions may be different, for example, in a long time evolution (Long Time Evolution, LTE) system, it is called eNodeB or eNB; in a 5G NR system, it is called gNodeB or gNB. With the evolution of communication technology, the name of "network device" may change. For convenience of description, the above-mentioned devices providing wireless communication function for the terminal device 10 are collectively referred to as network devices in the embodiments of the application.

[0047] In the embodiments of the present application, the terminal device 10 and the network device 20 both support MIMO function, i.e., the communication system is a MIMO system. In order to realize the MIMO function, the terminal device 10 and the network device 20 are both provided with multiple antennas, thereby forming a multi-channel antenna system in the process of transceiving.

[0048] Reference is made to Figure 2 which shows a flowchart of a signal demodulation method provided by an exemplary embodiment of the present application. The present embodiment takes the method used in a baseband chip as an example for illustration, and the method can include the following steps:

[0049] In step 201, channel estimation and noise estimation are performed on the received signal to obtain a channel matrix and an initial noise matrix.

[0050] In the process of signal transmission through a channel, the signal will be distorted or added with noise. In order to determine the characteristics of the channel through which the signal is transmitted, the baseband chip needs to perform channel estimation.

[0051] As to the specific way of channel estimation, in some embodiments, in the case of a known transmitted signal, a mathematical model is set up to make the transmitted signal related to the received signal. The mathematical model is a channel matrix composed of channel coefficients, which are channel gains.

[0052] Further, in order to determine the characteristics of the noise added in the signal, the baseband chip needs to perform noise estimation.

[0053] As to the specific way of noise estimation, in some embodiments, according to a known initial noise signal, an initial noise matrix is constructed with corresponding noise coefficients. The embodiments of the present application do not limit the specific ways of channel estimation and noise estimation.

[0054] In step 202, a noise matrix adjustment factor is determined based on the channel matrix.

[0055] Unlike the way of determining the noise matrix adjustment factor by using empirical values in the related art, in the present embodiment, the baseband chip determines the noise matrix adjustment factor based on the channel matrix.

[0056] The baseband chip obtains different channel matrices through channel estimation according to the channel transmission environment of different communication systems. Further, the baseband chip correspondingly determines the noise matrix adjustment factor according to the channel matrix.

[0057] Illustratively, the baseband chip determines the noise matrix adjustment factor according to special position elements of the channel matrix, such as diagonal elements; or the baseband chip first performs corresponding matrix operation processing on the channel matrix, and then determines the noise matrix adjustment factor according to special position elements of the obtained matrix.

[0058] In step 203, the initial noise matrix is adjusted based on the noise matrix adjustment factor to obtain a target noise matrix.

[0059] According to the rules of matrix operation, the baseband chip adjusts the initial noise matrix based on the noise matrix adjustment factor, and the noise matrix adjustment factor needs to be processed accordingly. For example, according to the properties of the initial noise matrix, a matrix related to the noise matrix adjustment factor is constructed, and then the target noise matrix is obtained by using matrix operation.

[0060] In step 204, the received signal is demodulated based on the channel matrix and the target noise matrix by using a target demodulation algorithm to obtain a signal demodulation result. The target demodulation algorithm involves a matrix inversion operation on a target matrix, which is determined based on the channel matrix and the target noise matrix.

[0061] The baseband chip constructs the target matrix in the target demodulation algorithm based on the channel matrix and the target noise matrix, and then demodulates the received signal by using the target demodulation algorithm to obtain a signal demodulation result.

[0062] In a possible implementation, the target demodulation algorithm for demodulating the received signal involves a matrix inversion operation, such as the MMSE algorithm or other improved algorithms based on the MMSE algorithm. Of course, any demodulation algorithm involving a matrix inversion operation can be regarded as a target demodulation algorithm, and the embodiments of the present application do not limit the specific demodulation algorithm.

[0063] It should be noted that, for the convenience of description, the following embodiments take the MMSE algorithm as an example for illustrative description, but do not limit the specific demodulation algorithm.

[0064] In summary, in the embodiments of the present application, the baseband chip estimates the channel and the noise of the received signal to obtain the channel matrix and the initial noise matrix, determines the noise matrix adjustment factor based on the channel matrix, adjusts the initial noise matrix based on the noise matrix adjustment factor to obtain the target noise matrix, and then demodulates the received signal by using the target demodulation algorithm based on the channel matrix and the target noise matrix. In the process of determining the noise matrix adjustment factor, the baseband chip takes the channel matrix as the adjustment basis, can dynamically change the noise matrix adjustment factor in different channel environments, thereby enhancing the stability of the matrix inversion in the target demodulation algorithm, and further improving the signal demodulation performance and the demodulation quality.

[0065] Please refer to Figure 3 which shows a flowchart of a signal demodulation method provided by another exemplary embodiment of the present application. The present embodiment takes the method for a baseband chip and based on the MMSE algorithm for signal demodulation as an example for description, and the method can include the following steps:

[0066] Step 301, channel estimation and noise estimation are performed on the received signal to obtain a channel matrix and an initial noise matrix.

[0067] The implementation of this step can refer to step 201 described above, and this embodiment will not be repeated here.

[0068] Step 302, based on the product of the channel matrix and the corresponding conjugate transpose matrix of the channel matrix, a positive semi-definite matrix is determined.

[0069] The baseband chip obtains the channel matrix through channel estimation according to the characteristics of the channel, wherein the number of rows of the channel matrix is the number of receive antennas, and the number of columns is the number of transmit antennas.

[0070] The baseband chip determines a positive semi-definite matrix based on the product of the channel matrix and the corresponding conjugate transpose matrix of the channel matrix, and the obtained positive semi-definite matrix is a square matrix, that is, the number of rows is equal to the number of columns.

[0071] Illustratively, H represents a channel matrix of size N Rx *N Tx , the channel matrix is multiplied by its corresponding conjugate transpose matrix to obtain A = HH H , wherein the positive semi-definite matrix A is an N Rx order matrix.

[0072] Step 303, based on the diagonal elements of the positive semi-definite matrix, a reference value of an adjustment factor is determined.

[0073] Generally, in the case that there is no correlation between the elements of the noise column vector, the baseband chip performs noise whitening processing on the received signal, and the obtained initial noise matrix is the product of the noise power and the unit matrix. Therefore, the baseband chip determines the reference value δ of the adjustment factor based on the diagonal elements of the positive semi-definite matrix, so as to adjust the initial noise matrix.

[0074] In one possible implementation, the baseband chip determines the maximum value of the diagonal elements of the positive semi-definite matrix as the reference value of the adjustment factor.

[0075] Illustratively, the positive semi-definite matrix is:

[0076]

[0077] The baseband chip takes the maximum value of the diagonal elements A nn of the positive semi-definite matrix A as the reference value δ of the adjustment factor:

[0078] δ = MAX(A 11 ,…,A nn )

[0079] In another possible implementation, the baseband chip determines the average of the diagonal elements of the positive semi-definite matrix as the adjustment factor reference value.

[0080] Illustratively, the baseband chip takes the average of all the diagonal elements A nn as the adjustment factor reference value δ:

[0081]

[0082] Of course, in other possible implementations, the baseband chip can determine the median value of the diagonal elements, etc., as the adjustment factor reference value, which is not limited in the present embodiment.

[0083] Step 304, based on the signal-to-noise ratio of the communication system, determine the reference value scaling factor corresponding to the adjustment factor reference value.

[0084] Since the adjustment factor reference value is directly determined according to the diagonal elements of the positive semi-definite matrix, in the case of high signal-to-noise ratio, the noise power itself is very small, and the value corresponding to the initial noise matrix is also very small. The baseband chip directly adjusts the initial noise matrix using the adjustment factor reference value, which will cause the value of the initial noise matrix to be multiplied. Therefore, the baseband chip needs to determine the reference value scaling factor β corresponding to the adjustment factor reference value based on the signal-to-noise ratio of the communication system.

[0085] In one possible implementation, the baseband chip determines the maximum signal-to-noise ratio that can be achieved by the communication system in which it is located; based on the maximum signal-to-noise ratio, determine the reference value scaling factor, and the reference value scaling factor is in a negative correlation relationship with the maximum signal-to-noise ratio.

[0086] The signal-to-noise ratio that the communication system can achieve is the largest when the system communication quality is in an ideal state, at which time the noise power is the smallest, and correspondingly, the adjustment factor reference value also needs to be correspondingly reduced. Therefore, the baseband chip determines the reference value scaling factor based on the maximum signal-to-noise ratio, which can achieve a better scaling effect.

[0087] Illustratively, the maximum signal-to-noise ratio that the system can achieve is SNR max dB, then the reference value scaling factor can be expressed as:

[0088]

[0089] Where M is the protection margin, and the typical range is [0, 6] dB.

[0090] However, in actual communication systems, there is a certain gap between the actual signal-to-noise ratio of the communication system and the maximum signal-to-noise ratio that can be achieved in an ideal state. Therefore, in order to further optimize the scaling effect of the adjustment factor reference value, the baseband chip can determine the reference value scaling factor based on the actual signal-to-noise ratio of the communication system.

[0091] In another possible implementation, the baseband chip determines a historical average signal-to-noise ratio of the communication system; and determines a reference value scaling factor based on the historical average signal-to-noise ratio, the reference value scaling factor being negatively correlated with the historical average signal-to-noise ratio.

[0092] The baseband chip determines the reference value scaling factor based on the historical average signal-to-noise ratio of the communication system for a period of time, so that the reference value of the adjustment factor can be scaled according to the actual situation.

[0093] For example, the maximum signal-to-noise ratio that can be achieved by the communication system in which the baseband chip is located is 120 dB, and the historical average signal-to-noise ratio of the communication system for a period of time is 110 dB. When the baseband chip demodulates the signal of the actual communication system, the reference value scaling factor can be determined based on the historical average signal-to-noise ratio 110 dB, and the reference value of the adjustment factor can be scaled.

[0094] In step 305, the noise matrix adjustment factor is determined based on the adjustment factor reference value and the reference value scaling factor.

[0095] The baseband chip determines the product of the adjustment factor reference value δ and the reference value scaling factor β as the noise matrix adjustment factor βδ.

[0096] In step 306, the noise adjustment matrix is generated based on the noise matrix adjustment factor, and the noise adjustment matrix is a diagonal matrix.

[0097] In general, the baseband chip performs noise whitening on the received signal, and the obtained initial noise matrix is the product of the noise power and the unit matrix, that is, a diagonal matrix.

[0098] Therefore, the baseband chip determines the noise adjustment matrix generated based on the noise matrix adjustment factor as a diagonal matrix, so as to effectively adjust the initial noise matrix.

[0099] For example, the baseband chip determines the product of the noise matrix adjustment factor and the unit matrix as the noise adjustment matrix, which can be represented as βδ·I, where I represents the unit matrix.

[0100] In step 307, the noise adjustment matrix and the initial noise matrix are superimposed to obtain the target noise matrix.

[0101] The baseband chip superimposes the noise adjustment matrix and the initial noise matrix to obtain the target noise matrix.

[0102] For example, the target noise matrix can be represented as: βδ·I+R nn , where R nn is the initial noise matrix. When the baseband chip performs noise whitening on the received signal, the target noise matrix can be represented as: βδ·I+σ 2 I, where σ2 Indicates noise power.

[0103] Step 308: Based on the channel matrix and the target noise matrix, the received signal is demodulated using a target demodulation algorithm to obtain the demodulation result. The target demodulation algorithm involves matrix inversion of the target matrix, which is determined based on the channel matrix and the target noise matrix.

[0104] Schematic representation: Based on the target noise matrix, the signal demodulation process using a target demodulation algorithm can be represented as follows:

[0105]

[0106] When the baseband chip performs noise whitening on the received signal, the process of signal demodulation using the target demodulation algorithm can be represented as:

[0107]

[0108] In this embodiment, the baseband chip determines a positive semi-definite matrix based on the product of the channel matrix and its corresponding conjugate transpose, and then determines the adjustment factor reference value based on the diagonal elements of the positive semi-definite matrix. Simultaneously, the baseband chip scales the adjustment factor reference value according to the signal-to-noise ratio (SNR) of the communication system to determine the noise adjustment matrix. By using the channel matrix and the SNR of the communication system as references in determining the noise adjustment matrix, the baseband chip can more reasonably determine the noise adjustment matrix, thereby ensuring the stability of the matrix inversion operation in the target demodulation algorithm.

[0109] Please refer to the above embodiments. Figure 4 The diagram illustrates an implementation schematic of a signal demodulation process provided in an exemplary embodiment of this application.

[0110] The baseband chip performs channel estimation and noise estimation on the received signal 41 to obtain the corresponding channel matrix 42 and initial noise matrix 43. Based on the channel matrix 42, it determines the noise matrix adjustment factor 44, and then uses the noise matrix adjustment factor 44 to adjust the initial noise matrix 43 to obtain the target noise matrix 45. Based on the channel matrix 42 and the target noise matrix 45, the baseband chip demodulates the received signal 41 using the MMSE demodulation algorithm 46 to obtain the demodulation result 47.

[0111] In the case of high signal-to-noise ratio, the initial noise matrix is ​​based on the noise power and has a small value. According to the properties of singular matrices, singular matrices are non-invertible matrices, and the larger the condition number of the matrix, the closer the matrix is ​​to singular. Therefore, in the target demodulation algorithm, the baseband chip needs to adjust the initial noise matrix to ensure the stability of matrix inversion of the target matrix.

[0112] Therefore, in a possible implementation, when the signal-to-noise ratio of the communication system in which the baseband chip is located is higher than the signal-to-noise ratio threshold, and the semi-positive definite matrix is close to singular, the baseband chip determines a noise matrix adjustment factor based on the channel matrix, so as to subsequently adjust the initial noise matrix based on the noise matrix adjustment factor, to ensure that the matrix inversion operation in the target demodulation algorithm can be stable.

[0113] In the above implementation, the baseband chip determines the ratio of the maximum eigenvalue to the minimum eigenvalue of the semi-positive definite matrix that can be stably inverted as a condition number threshold, and when the condition number of the semi-positive definite matrix is greater than the condition number threshold, the baseband chip determines that the semi-positive definite matrix is close to singular.

[0114] However, in a low signal-to-noise ratio environment (the initial noise matrix has a relatively large value), or the semi-positive definite matrix is not close to singular (is an invertible matrix), the matrix inversion operation in the target demodulation algorithm is relatively stable, and therefore, in order to reduce the amount of calculation, the baseband chip does not need to determine the noise matrix adjustment factor based on the channel matrix.

[0115] In a possible implementation, when the signal-to-noise ratio of the communication system in which the baseband chip is located is lower than the signal-to-noise ratio threshold, or the semi-positive definite matrix is not close to singular, the baseband chip performs signal demodulation on the received signal based on the channel matrix and the initial noise matrix by using the target demodulation algorithm, to obtain a signal demodulation result.

[0116] For example, when the signal-to-noise ratio is higher than 70 dB, and the condition number of the semi-positive definite matrix is greater than the condition number threshold, the baseband chip determines the noise matrix adjustment factor based on the channel matrix, and adjusts the initial noise matrix, to ensure the stability of the matrix inversion in the target demodulation algorithm.

[0117] When the signal-to-noise ratio is lower than 70 dB, or the condition number of the semi-positive definite matrix is less than the condition number threshold set by the system, the baseband chip directly performs signal demodulation on the received signal based on the channel matrix and the initial noise matrix by using the target demodulation algorithm.

[0118] In the above implementations, the baseband chip first determines whether to adjust the initial noise matrix according to the signal-to-noise ratio of the communication system in which the baseband chip is located and the singular property of the semi-positive definite matrix, and then performs signal demodulation on the received signal based on the target demodulation algorithm, which can reduce the amount of calculation while ensuring the stability of the matrix inversion operation.

[0119] In a possible implementation, the baseband chip supports at least two demodulation algorithms (including the target demodulation algorithm) and is capable of selecting different demodulation algorithms for signal demodulation according to different channel environments. In the case where the adopted demodulation algorithm is the target demodulation algorithm, the baseband chip determines the noise matrix adjustment factor based on the channel matrix. In the case where the adopted demodulation algorithm is not the target demodulation algorithm, the baseband chip does not need to determine the noise matrix adjustment factor based on the channel matrix.

[0120] For example, the demodulation algorithms supported by the baseband chip include TS_idealMod, TS_RobustQAM, and MMSE. When it is determined to adopt the MMSE algorithm based on the channel environment of the communication system in which the baseband chip is located, the baseband chip determines the noise matrix adjustment factor based on the channel matrix; when it is determined to adopt the TS_idealMod algorithm based on the channel environment of the communication system in which the baseband chip is located, the baseband chip does not need to determine the noise matrix adjustment factor based on the channel matrix.

[0121] For example, the demodulation algorithms supported by the baseband chip include TS_idealMod, TS_RobustQAM, and MMSE. When it is determined to adopt the MMSE algorithm based on the channel environment of the communication system in which the baseband chip is located, the baseband chip determines the noise matrix adjustment factor based on the channel matrix; when it is determined to adopt the TS_idealMod algorithm based on the channel environment of the communication system in which the baseband chip is located, the baseband chip does not need to determine the noise matrix adjustment factor based on the channel matrix. Figure 5

[0122] The estimation module 501 is configured to perform channel estimation and noise estimation on the received signal to obtain a channel matrix and an initial noise matrix.

[0123] The adjustment module 502 is configured to determine a noise matrix adjustment factor based on the channel matrix.

[0124] The adjustment module 502 is further configured to adjust the initial noise matrix based on the noise matrix adjustment factor to obtain a target noise matrix.

[0125] The demodulation module 503 is configured to perform signal demodulation on the received signal based on the channel matrix and the target noise matrix by using a target demodulation algorithm to obtain a signal demodulation result, wherein the target demodulation algorithm involves a matrix inversion operation on a target matrix, and the target matrix is determined based on the channel matrix and the target noise matrix.

[0126] Optionally, the adjustment module 502 is configured to:

[0127] determine a semi-positive definite matrix based on a product of the channel matrix and a conjugate transpose matrix corresponding to the channel matrix.

[0128] determine an adjustment factor reference value based on diagonal elements of the semi-positive definite matrix.

[0129] determine a reference value scaling factor corresponding to the adjustment factor reference value based on a signal-to-noise ratio of the communication system in which the baseband chip is located.

[0130] ​determine the noise matrix adjustment factor based on the adjustment factor reference value and the reference value scaling factor.

[0131] Optionally, the adjustment module 502 is configured to:

[0132] determine the maximum value of diagonal elements of the semi-positive definite matrix as the adjustment factor reference value;

[0133] or,

[0134] determine the average value of diagonal elements of the semi-positive definite matrix as the adjustment factor reference value.

[0135] Optionally, the adjustment module 502 is configured to:

[0136] determine the maximum signal-to-noise ratio achievable by the communication system; and determine the reference value scaling factor based on the maximum signal-to-noise ratio, the reference value scaling factor being negatively correlated with the maximum signal-to-noise ratio.

[0137] or,

[0138] determine the historical average signal-to-noise ratio of the communication system; and determine the reference value scaling factor based on the historical average signal-to-noise ratio, the reference value scaling factor being negatively correlated with the historical average signal-to-noise ratio.

[0139] Optionally, the adjustment module 502 is configured to:

[0140] generate a noise adjustment matrix based on the noise matrix adjustment factor, the noise adjustment matrix being a diagonal matrix.

[0141] perform matrix superposition on the noise adjustment matrix and the initial noise matrix to obtain the target noise matrix.

[0142] Optionally, the adjustment module 502 is configured to:

[0143] in a case where the signal-to-noise ratio of the communication system is higher than a signal-to-noise ratio threshold and the semi-positive definite matrix is close to singular, determine a noise matrix adjustment factor based on the channel matrix, the semi-positive definite matrix being a product of the channel matrix and a corresponding conjugate transpose matrix of the channel matrix.

[0144] Optionally, the demodulation module 503 is further configured to:

[0145] in a case where the signal-to-noise ratio of the communication system is lower than the signal-to-noise ratio threshold or the semi-positive definite matrix is not close to singular, perform signal demodulation on the received signal by the target demodulation algorithm based on the channel matrix and the initial noise matrix to obtain a signal demodulation result.

[0146] Optionally, the baseband chip supports at least two demodulation algorithms;

[0147] The adjustment module 502 is configured to:

[0148] In a case where the adopted demodulation algorithm is the target demodulation algorithm, a noise matrix adjustment factor is determined based on the channel matrix.

[0149] Optionally, the target demodulation algorithm is an MMSE algorithm.

[0150] In summary, in the embodiments of the present application, the baseband chip performs channel estimation and noise estimation on the received signal to obtain a channel matrix and an initial noise matrix, determines a noise matrix adjustment factor based on the channel matrix, adjusts the initial noise matrix with the noise matrix adjustment factor to obtain a target noise matrix, and then performs signal demodulation on the received signal by using the target demodulation algorithm based on the channel matrix and the target noise matrix. In the process of determining the noise matrix adjustment factor, the baseband chip takes the channel matrix as the adjustment basis, can dynamically change the noise matrix adjustment factor in different channel environments, thereby enhancing the stability of matrix inversion in the target demodulation algorithm, and further improving the signal demodulation performance and demodulation quality.

[0151] Please refer to Figure 6 which shows a structure block diagram of a terminal device provided by an example embodiment of the present application. The terminal device in the present application can include one or more of the following components: a processor 1210 and a memory 1220.

[0152] Optionally, the processor 1210 utilizes various interfaces and lines to connect various parts within the entire terminal device, and performs various functions of the terminal device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 1220, and calling data stored in the memory 1220. Optionally, the processor 1210 can be implemented in at least one of a hardware form of a digital signal processing (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA). The processor 1210 can be integrated with one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), a neural-network processing unit (NPU) and a baseband chip. Among them, the CPU is mainly used to process operating systems, user interfaces and application programs, etc.; the GPU is used to render and draw the content to be displayed on the touch display screen; the NPU is used to implement artificial intelligence (AI) functions; and the baseband chip is used to process wireless communication. It can be understood that the above baseband chip can also not be integrated into the processor 1210, but be implemented by a separate chip.

[0153] The memory 1220 can include a random access memory (RAM) and can also include a read-only memory (ROM). Optionally, the memory 1220 includes a non-transitory computer-readable storage medium. The memory 1220 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1220 can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing various method embodiments described below, etc.; and the data storage area can store data created according to the use of the terminal device (such as audio data, a phone book, etc.).

[0154] In addition, those skilled in the art can understand that the structure of the terminal device shown in the above-mentioned drawings does not constitute a limitation on the terminal device, and the terminal device can include more or fewer components than the drawings, or combine certain components, or different component arrangements. For example, the terminal device also includes display components, input units, sensors, audio circuits, speakers, microphones, power supplies, and the like, which are not described herein.

[0155] The embodiment of the present application further provides a baseband chip, which comprises a programmable logic circuit and / or program instructions, and when the baseband chip is running, is used for realizing the signal demodulation method provided by the above-mentioned embodiment.

[0156] The embodiment of the present application further provides a computer readable storage medium, which stores at least one program, and the at least one program is used for being executed by a processor to realize the signal demodulation method described in the above-mentioned embodiment.

[0157] The embodiment of the present application provides a computer program product, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device executes the signal demodulation method provided by the above-mentioned embodiment.

[0158] Those skilled in the art should realize that, in the above-mentioned one or more examples, the functions described in the embodiment of the present application can be realized by hardware, software, firmware or any combination thereof. When realized by software, these functions can be stored in a computer readable medium or transmitted as one or more instructions or codes on a computer readable medium. The computer readable medium includes a computer storage medium and a communication medium, wherein the communication medium includes any medium facilitating the transmission of computer programs from one place to another. The storage medium can be any available medium accessible by a general or special purpose computer.

[0159] The above-mentioned is only the optional embodiment of the present application, and does not limit the present application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A signal demodulation method characterized by comprising: The method comprises: channel estimation and noise estimation on the received signal to obtain a channel matrix and an initial noise matrix; determining a semi-positive definite matrix based on the product of the channel matrix and the corresponding conjugate transpose matrix of the channel matrix, determining an adjustment factor reference value based on the diagonal elements of the semi-positive definite matrix, determining a reference value scaling factor corresponding to the adjustment factor reference value based on the signal-to-noise ratio of the communication system, and determining the product of the adjustment factor reference value and the reference value scaling factor as the noise matrix adjustment factor; generating a noise adjustment matrix based on the noise matrix adjustment factor, the noise adjustment matrix being a diagonal matrix; and performing matrix superposition on the noise adjustment matrix and the initial noise matrix to obtain a target noise matrix; performing signal demodulation on the received signal based on the channel matrix and the target noise matrix by a target demodulation algorithm to obtain a signal demodulation result, the target demodulation algorithm involving a matrix inversion operation on a target matrix determined based on the channel matrix and the target noise matrix.

2. The method of claim 1, wherein, The method further comprises: determining the adjustment factor reference value based on the diagonal elements of the semi-positive definite matrix, comprising: determining the maximum value of the diagonal elements of the semi-positive definite matrix as the adjustment factor reference value; or, 3. The method of claim 1, wherein, determining the average value of the diagonal elements of the semi-positive definite matrix as the adjustment factor reference value. The method further comprises: determining the reference value scaling factor corresponding to the adjustment factor reference value based on the signal-to-noise ratio of the communication system, comprising: determining the maximum signal-to-noise ratio that can be achieved by the communication system, and determining the reference value scaling factor based on the maximum signal-to-noise ratio, the reference value scaling factor being negatively correlated with the maximum signal-to-noise ratio; 4. The method according to any one of claims 1 to 3, characterized in that, or, determining the historical average signal-to-noise ratio of the communication system, and determining the reference value scaling factor based on the historical average signal-to-noise ratio, the reference value scaling factor being negatively correlated with the historical average signal-to-noise ratio.

5. The method of claim 4, wherein, The method further comprises: in the case where the signal-to-noise ratio of the communication system is higher than a signal-to-noise ratio threshold and the semi-positive definite matrix is close to singular, determining the product of the adjustment factor reference value and the reference value scaling factor as the noise matrix adjustment factor, the semi-positive definite matrix being the product of the channel matrix and the corresponding conjugate transpose matrix of the channel matrix.

6. The method according to any one of claims 1 to 3, characterized in that, The method further comprises: in the case where the signal-to-noise ratio of the communication system is lower than the signal-to-noise ratio threshold or the semi-positive definite matrix is not close to singular, performing signal demodulation on the received signal based on the channel matrix and the initial noise matrix by the target demodulation algorithm to obtain a signal demodulation result. The baseband chip supports at least two demodulation algorithms.

7. The method according to any one of claims 1 to 3, characterized in that, The method further comprises:

8. A signal demodulation apparatus characterized by comprising: in the case where the adopted demodulation algorithm is the target demodulation algorithm, determining the noise matrix adjustment factor based on the adjustment factor reference value and the reference value scaling factor. The target demodulation algorithm is a minimum mean square error (MMSE) algorithm. The apparatus comprises: An estimation module is configured to perform channel estimation and noise estimation on the received signal to obtain a channel matrix and an initial noise matrix; An adjustment module is configured to determine a semi-definite matrix based on a product of the channel matrix and a conjugate transpose matrix corresponding to the channel matrix, determine an adjustment factor reference value based on diagonal elements of the semi-definite matrix, determine a reference value scaling factor corresponding to the adjustment factor reference value based on a signal-to-noise ratio of a communication system, and determine a noise matrix adjustment factor as a product of the adjustment factor reference value and the reference value scaling factor; The adjustment module is further configured to generate a noise adjustment matrix based on the noise matrix adjustment factor, the noise adjustment matrix being a diagonal matrix, and obtain a target noise matrix by performing matrix superposition on the noise adjustment matrix and the initial noise matrix. A demodulation module is configured to perform signal demodulation on the received signal by a target demodulation algorithm based on the channel matrix and the target noise matrix to obtain a signal demodulation result, the target demodulation algorithm involving a matrix inversion operation on a target matrix, the target matrix being determined based on the channel matrix and the target noise matrix.

9. A baseband chip, comprising: The baseband chip includes a programmable logic circuit and / or program instructions, and when the baseband chip is running, is configured to implement the signal demodulation method according to any one of claims 1 to 7.

10. A terminal device, comprising: The terminal device is provided with the baseband chip according to claim 9.

11. A computer readable storage medium, characterized in that, The storage medium stores at least one program, and the at least one program is configured to be executed by a processor to implement the signal demodulation method according to any one of claims 1 to 7.

12. A computer program product, characterised in that, The computer program product includes computer instructions stored in a computer readable storage medium, and a processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device implements the signal demodulation method according to any one of claims 1 to 7.

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