Channel quality optimization method based on wireless communication
By acquiring and optimizing channel state feedback information in the wireless communication system, including calculating the channel state information correlation degree and performing low-rank approximation processing, the problems of channel state information feedback delay and network burden in the prior art are solved, and more efficient channel quality optimization is achieved.
Patent Information
- Application Number
- CN202411708619.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-27
- Publication Date
- 2025-02-25
AI Technical Summary
When feedback of channel state information in the prior art, the network burden is heavy, resulting in unsatisfactory channel quality optimization results and strong delay.
By obtaining channel state feedback information, including the average channel gain and line-of-sight angle components, calculating the channel state information correlation degree between multiple users, comparing and combining channel state feedback information, and using low-rank approximation processing to optimize channel state feedback information.
It effectively reduces the network burden, improves the effect of channel quality optimization, reduces the content that each user needs to feedback, optimizes the efficiency of network resources, and reduces latency.
Smart Images
Figure CN119519789A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of channel quality optimization, and in particular to a channel quality optimization method based on wireless communication. Background Art
[0002] With the development of technology, wireless communication has evolved from analog communication to digital communication. Using digital signals for communication has the advantages of high precision, strong reliability, and good anti-interference performance. The application of digital communication technology in the fields of mobile communication and satellite communication has greatly promoted the development of wireless communication and improved the quality and speed of communication. Wireless communication is a communication method that uses the characteristics of electromagnetic wave signals that can propagate in free space to exchange information. Compared with wired communication methods, wireless communication does not have complicated wiring problems and can effectively reduce the complexity of the system.
[0003] Among them, channel quality is crucial in wireless communications. It directly affects data transmission rate, error rate and connection stability. High-quality channels can support faster data transmission and lower bit error rate, while allowing the use of more complex modulation methods to optimize communication performance. Changes in channel quality also affect resource allocation and interference management strategies. Therefore, channel quality is the ultimate goal for improving the efficiency and reliability of wireless communication systems.
[0004] Most of the existing channel quality optimization systems are implemented through channel state information feedback. In communication systems, channel state information feedback is widely used in wireless communication networks, especially in 5G networks. Through channel state information feedback, the network can optimize the signal transmission process, increase data transmission speed, reduce latency and improve reliability, thereby achieving the effect of optimizing channel quality.
[0005] However, the prior art requires the transmission of a large amount of channel status information when feeding back the channel status, which results in a heavy burden on the network, thus resulting in unsatisfactory effects in improving the channel quality.
[0006] In the prior art, there is a problem of high delay in feedback of channel state information. Summary of the invention
[0007] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a channel quality optimization method based on wireless communication, which solves the problem of high delay in channel state information feedback in the prior art by reducing the network burden.
[0008] To achieve the above object, the present invention provides the following technical solutions: A channel quality optimization method based on wireless communication comprises the following steps: obtaining channel state feedback information, wherein the channel state feedback information comprises an average channel gain and a sight angle component; calculating the channel state information correlation degree between multiple users based on a preset correlation model; comparing the channel state feedback information and the channel state information correlation degree, and obtaining the channel state feedback information to be merged according to the comparison result; and performing low-rank approximation processing on the channel state feedback information to be merged, and obtaining the optimized channel state feedback information.
[0009] In a preferred embodiment, the calculation of the channel state information correlation degree between multiple users is specifically: obtaining a measurement subset of a channel state information reference signal port, wherein the measurement subset of the channel state information reference signal port is calculated by the total number of channel state information reference signal ports and a ratio value; determining a precoding matrix based on the obtained measurement subset of the channel state information reference signal port; obtaining a correlation matrix in combination with the precoding matrix, calculating the rank of the correlation matrix, and obtaining the channel state information correlation degree.
[0010] In a preferred embodiment, the channel state feedback information and the channel state information correlation degree are compared, and the channel state feedback information to be merged is obtained according to the comparison result, specifically: channel state feedback information is obtained from user equipment of multiple channels, and the data format of the obtained channel state feedback information is processed in a unified format; the channel state feedback information in the unified format is combined with the channel state information correlation degree, and the state matching degree between channels is calculated based on the Pearson correlation coefficient; the calculated state matching degree between channels is compared with a preset standard threshold, and the channel state feedback information between channels that is higher than the preset standard threshold is shared and merged.
[0011] In a preferred embodiment, the channel state feedback information to be merged is subjected to low-rank approximation processing, and the processing method is as follows: obtaining the precoding matrix of the channel state feedback information to be merged whose comparison result with the channel state information correlation degree is higher than a preset threshold, and merging the compared precoding matrices to obtain a feedback matrix; performing singular value decomposition on the feedback matrix, and retaining the first r largest singular values, constructing an approximate matrix, and obtaining the optimized channel state feedback information.
[0012] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: Through the channel quality optimization method based on wireless communication, the correlation degree of channel state information between multiple users can be calculated, thereby further improving the effectiveness of shared feedback information and effectively solving the problem of strong delay in channel state information feedback in the prior art. By introducing the calculation of average channel gain and line of sight angle components, a more comprehensive channel state feedback than a single parameter is provided, thereby achieving a more accurate assessment of channel quality. Through low-rank approximation technology, important features in the channel state feedback information are retained, thereby effectively reducing redundancy and improving data processing efficiency. By merging channel state feedback information from multiple users, the content that each user needs to feedback is reduced, thereby optimizing the efficiency of network resource utilization. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 A flow chart of a channel quality optimization method based on wireless communication provided in an embodiment of the present application; DETAILED DESCRIPTION The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0013] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.
[0014] Embodiment 1, Figure 1 The present invention provides a channel quality optimization method based on wireless communication, comprising the following steps: S1 obtains channel state feedback information, where the channel state feedback information includes an average channel gain and a sight angle component; The average channel gain reflects the overall transmission performance of the channel, and refers to the average value of the power of the received signal relative to the power of the transmitted signal after the signal passes through the wireless channel within a specific time period.
[0015] The calculation formula of the average channel gain is as follows:
[0016] Where: E is the average channel gain, A is the direct signal amplitude, which indicates the direct signal strength from the transmitter, It represents the power of the scattered signal and the signal strength of different reflection paths in multipath propagation.
[0017] It should be noted that the size of the average channel gain directly affects the signal quality and coverage range of the system. The higher the average channel gain, the stronger the received signal, and the higher the transmission reliability and speed. The lower the average channel gain, the weaker the received signal, and the lower the transmission reliability and speed.
[0018] By averaging channel gain, the system can adjust resource allocation in real time to ensure that users can obtain higher transmission rates during periods of better channel conditions.
[0019] The line of sight angle component refers to the angle information in the signal propagation path from the transmitter to the receiver. The line of sight angle component includes the arrival angle and the emission angle. The arrival angle refers to the angle at which the signal reaches the receiver. The size of the arrival angle affects the phase and gain of the received signal. The emission angle refers to the angle at which the signal is emitted from the transmitter. The emission angle signal propagation characteristics.
[0020] The calculation formula of the arrival angle is as follows:
[0021] Where: is the angle of arrival, which describes the angle at which the signal reaches the receiver, are the coordinates of the transmitter, are the coordinates of the receiver.
[0022] The calculation formula of the emission angle is as follows:
[0023] Where: is the emission angle, which describes the angle at which the signal is emitted from the transmitter, are the coordinates of the transmitter, are the coordinates of the receiver.
[0024] It should be noted that the line-of-sight angle component is used in beamforming technology to enhance the directivity of the signal and improve the strength and quality of the received signal.
[0025] The channel state feedback information has the following effects on estimating channel quality: Signal quality: The size of the line-of-sight angle component affects the signal propagation path and multipath effect. Optimizing AoA and AoD helps reduce signal interference and improve the strength and quality of received signals; Antenna design: In MIMO systems, AoA and AoD can help design more efficient antenna arrays, thereby improving system capacity and coverage.
[0026] Resource allocation: The line-of-sight angle information contained in the channel state feedback can be used to dynamically adjust the transmit power and select the appropriate modulation method to adapt to changing channel conditions.
[0027] S2 calculates the correlation degree of channel state information between multiple users based on a preset correlation model; The step of calculating the correlation degree of channel state information between multiple users comprises the following steps: Acquire a measurement subset of a channel state information reference signal port, where the measurement subset of the channel state information reference signal port is calculated by a total number of channel state information reference signal ports and a ratio value; Determining a precoding matrix based on a measurement subset of the acquired channel state information reference signal port; In combination with the precoding matrix, a correlation matrix is obtained, the rank of the correlation matrix is calculated, and the channel state information correlation degree is obtained.
[0028] It should be noted that the ratio value is usually indicated by high-layer signaling, and the value range is greater than 0 and less than or equal to 1.
[0029] The measurement subset of the channel state information reference signal port is specifically:
[0030] Wherein: M is the measurement subset of the channel state information reference signal port, r is the ratio value indicated by the high-layer signaling, and N is the total number of channel state information reference signal ports.
[0031] The precoding matrix is defined as follows:
[0032] Where: is the precoding matrix, represents the channel gain from the i-th transmitter to the j-th receiver, and M is the measurement subset of the channel state information reference signal port.
[0033] The correlation matrix is defined as follows:
[0034] Where: is the correlation matrix, is the identity matrix, is the precoding matrix, is the conjugate transpose of the precoding matrix.
[0035] The channel state information correlation degree is calculated by the following formula:
[0036] Where: K is the correlation degree of channel state information, represents the channel gain from the i-th transmitter to the j-th receiver, is the rank of the correlation matrix of the channel transmitted through the nth channel state information reference signal port, is the rank of the correlation matrix of the channel transmitted through the n+1th channel state information reference signal port, and N is the total number of channel state information reference signal ports.
[0037] The ratio value is used to measure resource utilization in communication networks, and is also used to quantify the proportion of a specific parameter to the whole. It is usually expressed as a floating value between 0 and 1. The value in between indicates the degree of existence of the part. The closer the value is to 1, the higher the proportion of the part to the whole.
[0038] The precoding matrix is a linear transformation matrix used to process signals in a multi-antenna system. The design of the precoding matrix is based on channel characteristics and is determined by measuring subsets. The selection of the precoding matrix is based on the UE's measurement and estimation of channel characteristics, including spatial channel response, etc.
[0039] S3 compares the channel state feedback information and the channel state information correlation degree, and obtains the channel state feedback information to be merged according to the comparison result; The comparing the channel state feedback information and the channel state information correlation degree, and obtaining the channel state feedback information to be combined according to the comparing result, is specifically: Acquire channel state feedback information from user equipments of multiple channels, and perform unified format processing on the data formats of the acquired channel state feedback information; The unified format of the channel state feedback information is combined with the channel state information correlation degree, and the state matching degree between channels is calculated based on the Pearson correlation coefficient; The calculated state matching degree between channels is compared with a preset standard threshold, and the channel state feedback information between channels that is higher than the preset standard threshold is shared and merged.
[0040] The state matching degree between channels is calculated based on the Pearson correlation coefficient, and the calculation formula is as follows:
[0041] Where: X is the feedback information of channel 1, Y is the feedback information of channel 2, is the mean value of the feedback information of channel 1, is the mean of the feedback information of channel 2.
[0042] The channel state feedback information between channels that are higher than the preset standard threshold is shared and merged. After determining the channels to be merged, the feedback information of the channels needs to be weighted averaged. The weighted average formula is as follows:
[0043] Where: is the frequency response of the ith channel, is the weight corresponding to the i-th channel.
[0044] It should be noted that the weight corresponding to the i-th channel is set based on the signal-to-noise ratio of the channel.
[0045] Sharing channel state feedback information reduces the amount of feedback that each user needs to provide, which has the following importance: Reduce feedback burden: By combining feedback information from multiple users, the amount of feedback that each user needs to provide can be reduced, thereby reducing the burden on the uplink. Improve system efficiency: Combining feedback information can improve the base station's overall perception of channel status, which helps optimize resource allocation and scheduling strategies; Reduce latency: Reducing the content of feedback can shorten feedback time, reduce system latency, and improve real-time performance.
[0046] S4 performs low-rank approximation processing on the channel state feedback information to be combined to obtain optimized channel state feedback information.
[0047] Low-rank approximation refers to extracting the main components from high-dimensional data to simplify information and remove redundancy. Through low-rank approximation, important features in channel state feedback information can be retained to achieve the purpose of information compression.
[0048] The low-rank approximation processing is performed on the channel state feedback information to be combined, and the processing method is as follows: Acquire the precoding matrix of the channel state feedback information to be merged, the comparison result of which between the channel state feedback information and the channel state information correlation degree is higher than a preset threshold, and merge the precoding matrices to be compared to obtain a feedback matrix; The feedback matrix is subjected to singular value decomposition, and the first r largest singular values are retained to construct an approximate matrix to obtain optimized channel state feedback information.
[0049] The singular value decomposition processing formula is as follows:
[0050] Where: M is the feedback matrix, is the first r rows of the precoding matrix, is the first r columns of the precoding matrix, is a diagonal matrix containing singular values, is an approximate matrix.
[0051] Singular value decomposition can achieve data dimensionality reduction by retaining the largest r singular values and corresponding singular vectors to obtain an approximate matrix, which provides the best low-rank approximation, meaning that among all matrices of rank r, the difference between the obtained approximate matrix and the original matrix is the smallest.
[0052] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.
[0053] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.
[0054] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.
[0055] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.
[0056] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
[0057] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
Claims
1. A channel quality optimization method based on wireless communication, characterized in that: The following steps are involved: Acquiring channel state feedback information, wherein the channel state feedback information includes an average channel gain and a sight angle component; Calculate the correlation degree of channel state information between multiple users based on a preset correlation model; Comparing the channel state feedback information and the channel state information correlation degree, and obtaining the channel state feedback information to be merged according to the comparison result; The channel state feedback information to be combined is processed by low rank approximation to obtain optimized channel state feedback information.
2. The channel quality optimization method based on wireless communication according to claim 1, characterized in that: The calculating of the correlation degree of the channel state information between multiple users is specifically: Acquire a measurement subset of a channel state information reference signal port, where the measurement subset of the channel state information reference signal port is calculated by a total number of channel state information reference signal ports and a ratio value; Determine a precoding matrix based on a measurement subset of the acquired channel state information reference signal port; In combination with the precoding matrix, a correlation matrix is obtained, the rank of the correlation matrix is calculated, and the channel state information correlation degree is obtained.
3. The channel quality optimization method based on wireless communication as claimed in claim 2, characterized in that: The comparing the channel state feedback information and the channel state information correlation degree, and obtaining the channel state feedback information to be combined according to the comparing result, is specifically: Acquire channel state feedback information from user equipments of multiple channels, and perform unified format processing on the data formats of the acquired channel state feedback information; The unified format of the channel state feedback information is combined with the channel state information correlation degree, and the state matching degree between channels is calculated based on the Pearson correlation coefficient; The calculated state matching degree between channels is compared with a preset standard threshold, and the channel state feedback information between channels that is higher than the preset standard threshold is shared and merged.
4. The channel quality optimization method based on wireless communication as claimed in claim 3, characterized in that: The low-rank approximation processing is performed on the channel state feedback information to be combined, and the processing method is as follows: Acquire the precoding matrix of the channel state feedback information to be merged, the comparison result of which between the channel state feedback information and the channel state information correlation degree is higher than a preset threshold, and merge the precoding matrices to be compared to obtain a feedback matrix; The feedback matrix is subjected to singular value decomposition, and the first r largest singular values are retained to construct an approximate matrix to obtain optimized channel state feedback information.
5. The channel quality optimization method based on wireless communication according to claim 4, characterized in that: The calculation formula of the average channel gain is as follows: Where: E is the average channel gain, A is the direct signal amplitude, which indicates the direct signal strength from the transmitter, It represents the power of the scattered signal and the signal strength of different reflection paths in multipath propagation.
6. The channel quality optimization method based on wireless communication according to claim 5, characterized in that: The sight angle component includes the arrival angle and the emission angle. The specific calculation formulas of the arrival angle and the emission angle are as follows: Where: is the angle of arrival, which describes the angle at which the signal reaches the receiver, are the coordinates of the transmitter, are the coordinates of the receiver, is the launch angle, which describes the angle at which the signal is emitted from the transmitter.
7. The channel quality optimization method based on wireless communication according to claim 6, characterized in that: The channel state information correlation degree is calculated by the following formula: Where: K is the correlation degree of channel state information, represents the channel gain from the i-th transmitter to the j-th receiver, is the rank of the correlation matrix of the channel transmitted through the nth channel state information reference signal port, is the rank of the correlation matrix of the channel transmitted through the n+1th channel state information reference signal port, and N is the total number of channel state information reference signal ports.
8. The channel quality optimization method based on wireless communication according to claim 7, characterized in that: The state matching degree between channels is calculated based on the Pearson correlation coefficient, and the calculation formula is as follows: Where: X is the feedback information of channel 1, Y is the feedback information of channel 2, is the mean value of the feedback information of channel 1, is the mean of the feedback information of channel 2.
9. The channel quality optimization method based on wireless communication according to claim 8, characterized in that: The channel state feedback information between channels with a value higher than a preset standard threshold is shared and merged, specifically: Where: is the frequency response of the ith channel, is the weight corresponding to the i-th channel.
10. The channel quality optimization method based on wireless communication according to claim 9, characterized in that: Singular value decomposition, the processing formula is as follows: Where: M is the feedback matrix, is the first r rows of the precoding matrix, is the first r columns of the precoding matrix, is a diagonal matrix containing singular values, is an approximate matrix.