Uplink data transmission method, device, equipment, storage medium and product

Abstract

The invention discloses an uplink data transmission method, device and equipment, a storage medium and a product, and relates to the technical field of 5G communication, and the uplink data transmission method comprises the following steps: obtaining channel state information of a plurality of target users; based on the channel state information, performing frequency band grouping processing on each target user to obtain a plurality of user resource groups; according to the channel gain in each user resource group, power distribution is carried out on each target user, and the optimal transmitting power of each user is obtained; and dynamically adjusting the user resource groups and the optimal transmitting power based on real-time channel state information and a preset service quality requirement so as to perform data transmission on each user. The spectrum resource utilization rate is improved.

Description

Technical Field

[0001] The present application relates to the field of 5G communication technology, and in particular to an uplink data transmission method, apparatus, device, storage medium and computer program product. Background Art

[0002] With the development of 5G communication technology, how to support more users to communicate with high quality under limited spectrum resources has become an important technical problem. Traditional multiple access technologies, such as orthogonal frequency division multiple access (OFDMA) and code division multiple access (CDMA), have limitations in spectrum utilization and system capacity, and are difficult to meet the 5G system's requirements for high spectrum efficiency and large-scale connections. This results in low spectrum resource utilization, affecting signal quality and communication reliability.

[0003] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of this application is to provide an invention name, which aims to solve the technical problems in related technologies that are limited in spectrum utilization and system capacity and difficult to meet the requirements of 5G systems for high spectrum efficiency and large-scale connections.

[0005] To achieve the above object, the present application proposes an uplink data transmission method, the uplink data transmission method comprising:

[0006] Obtain channel state information of multiple target users;

[0007] Based on the channel state information, frequency band grouping processing is performed on each target user to obtain multiple user resource groups;

[0008] Allocating power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power for each user;

[0009] Based on the real-time channel state information and the preset service quality requirement, the user resource grouping and the optimal transmission power are dynamically adjusted to transmit data to each of the users.

[0010] In one embodiment, the step of performing frequency band grouping processing on each target user based on the channel state information to obtain multiple user resource groups includes:

[0011] Based on the channel state information, determine the channel gain and signal-to-noise ratio information of each target user;

[0012] Based on the grouping algorithm of channel similarity, channel gain and signal-to-noise ratio information, each of the target users is assigned to a group to obtain a plurality of user resource groups, wherein the target users in each user resource group share the same frequency band resources.

[0013] In one embodiment, the step of allocating power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power of each target user includes:

[0014] Based on the channel gain of each target user in the user resource group, the optimal transmission power of each target user is calculated by a power allocation algorithm to distinguish the transmission signals of the target users in each user resource group.

[0015] In one embodiment, the step of dynamically adjusting the user resource grouping and the optimal transmit power based on the real-time channel state information and the preset service quality requirement includes:

[0016] Based on a preset dynamic optimization function, real-time channel state information and preset service quality requirements, the user resource grouping and the optimal transmission power are optimized to obtain an optimization result;

[0017] Selecting the best user resource grouping and power allocation strategy from each of the optimization results, and applying the best user resource grouping and power allocation scheme to the current time slot;

[0018] The channel state information and the service quality requirements of the target user are monitored in real time. If changes are detected in the channel state information or the service quality requirements, the user resource grouping and power allocation strategy are dynamically adjusted again.

[0019] In one embodiment, before the step of dynamically adjusting the user resource grouping and the optimal transmit power based on the real-time channel state information and the preset service quality requirement, the method further includes:

[0020] Obtaining mixed signals of each user in the uplink;

[0021] Based on the interference detection algorithm, the mixed signal is separated and processed to obtain an interference signal and a target signal;

[0022] Based on the interference suppression algorithm, the interference signal is filtered and signal separated to reduce the interference degree of the interference signal on the target signal.

[0023] In one embodiment, the step of performing separation processing on the mixed signal based on the interference detection algorithm to obtain the interference signal and the target signal includes:

[0024] Preprocessing the mixed signal to obtain a preprocessed signal;

[0025] Analyzing the preprocessed signal by a blind source separation algorithm to obtain an autocorrelation matrix of the mixed signal;

[0026] Iteratively calculating the autocorrelation matrix through a nonlinear function selection mechanism to separate the target signal component and the interference signal component;

[0027] From the target signal component and the interference signal component, a signal component whose characteristic value is greater than a first preset threshold is selected as the target signal, and a signal component whose characteristic value is less than a second preset threshold is selected as the interference signal, wherein the first preset threshold is greater than the second preset threshold.

[0028] In addition, to achieve the above-mentioned purpose, the present application also proposes an uplink data transmission device, the uplink data transmission device comprising:

[0029] A first acquisition module, used to acquire channel state information of multiple target users;

[0030] A processing module, configured to perform frequency band grouping processing on each target user based on the channel state information to obtain multiple user resource groups;

[0031] An allocation module, configured to allocate power to each target user according to the channel gain in each user resource group, so as to obtain the optimal transmission power for each user;

[0032] The adjustment module is used to dynamically adjust the user resource grouping and the optimal transmission power based on real-time channel state information and preset service quality requirements to transmit data to each user.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes an uplink data transmission device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the uplink data transmission method as described above.

[0034] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the uplink data transmission method described above are implemented.

[0035] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the uplink data transmission method as described above are implemented.

[0036] The present application proposes an uplink data transmission method, apparatus, device, storage medium and computer program product. The present application obtains channel state information of multiple target users, performs frequency band grouping processing on each target user based on the channel state information, obtains multiple user resource groups, allocates power to each target user according to the channel gain in each user resource group, calculates the optimal transmission power of each target user, and dynamically adjusts the user resource grouping and the optimal transmission power based on real-time channel state information and preset service quality requirements; the dynamic adjustment can improve the flexibility and adaptability of channel data transmission, can quickly respond to changes in channel status and user needs, improve spectrum resource utilization, and optimize system performance and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0039] Figure 1 A flowchart of the first embodiment of the uplink data transmission method of the present application is provided;

[0040] Figure 2 A flowchart of the second embodiment of the uplink data transmission method of the present application is provided;

[0041] Figure 3 A schematic diagram of the overall execution flow involved in the uplink data transmission method of the present application;

[0042] Figure 4 This is a schematic diagram of the module structure of the uplink data transmission device according to an embodiment of the present application;

[0043] Figure 5 A schematic diagram of the device structure of the hardware operating environment involved in the uplink data transmission method in the embodiment of the present application.

[0044] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0046] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0047] The main solutions of the embodiments of this application are:

[0048] Obtain channel state information of multiple target users;

[0049] Based on the channel state information, frequency band grouping processing is performed on each target user to obtain multiple user resource groups;

[0050] Allocating power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power for each user;

[0051] Based on the real-time channel state information and the preset service quality requirement, the user resource grouping and the optimal transmission power are dynamically adjusted to transmit data to each of the users.

[0052] Because traditional multiple access technologies, such as Orthogonal Frequency Division Multiple Access (OFDMA) and Code Division Multiple Access (CDMA), have limitations in spectrum utilization and system capacity, it is difficult to meet the 5G system's requirements for high spectrum efficiency and large-scale connections.

[0053] The present application proposes an uplink data transmission method, apparatus, device, storage medium and computer program product. The present application obtains channel state information of multiple target users, performs frequency band grouping processing on each target user based on the channel state information, obtains multiple user resource groups, allocates power to each target user according to the channel gain in each user resource group, calculates the optimal transmission power of each target user, and dynamically adjusts the user resource grouping and the optimal transmission power based on real-time channel state information and preset service quality requirements; the dynamic adjustment can improve the flexibility and adaptability of channel data transmission, can quickly respond to changes in channel status and user needs, improve spectrum resource utilization, and optimize system performance and user experience.

[0054] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, an uplink data transmission device, a base station, etc. The following takes a base station as an example to illustrate this embodiment and the following embodiments.

[0055] Based on this, the embodiment of the present application provides an uplink data transmission method, referring to Figure 1 , Figure 1This is a flowchart of the first embodiment of the uplink data transmission method of the present application.

[0056] In this embodiment, the uplink data transmission method includes steps S10 to S40:

[0057] Step S10, obtaining channel state information of multiple target users;

[0058] It should be noted that the channel state information includes the uplink pilot signal of the target user. In the process of collecting channel state information, the channel state information collection module in the base station is initialized, and the parameters including the collection period, pilot signal length and sampling rate are set. After the parameters of these collection signals are set, signal collection is performed on the target user who has established a connection with the current base station.

[0059] It should be noted that the solution of the present application is implemented based on the technology of non-orthogonal multiple access technology (NOMA). As a new multiple access technology, non-orthogonal multiple access technology (NOMA) can distinguish users in the power domain or code domain to enable multiple users to communicate in the same frequency band, thereby effectively improving the spectrum efficiency and system capacity.

[0060] Step S20, performing frequency band grouping processing on each target user based on the channel state information to obtain multiple user resource groups;

[0061] It should be noted that based on the channel state information, the user's channel gain and signal-to-noise ratio information are used to group users, and a grouping algorithm based on channel similarity is adopted to assign users with similar channel gain and signal-to-noise ratio to the same group. Users in each group share the same frequency band resources.

[0062] It should be noted that user resource grouping is obtained by grouping each user based on frequency band resources. The purpose is to avoid channel congestion when multiple users transmit at the same time, and to allocate users to corresponding frequency bands to improve spectrum utilization.

[0063] In a feasible implementation manner, the step S20 of performing frequency band grouping processing on each target user based on the channel state information to obtain multiple user resource groups includes:

[0064] Based on the channel state information, determine the channel gain and signal-to-noise ratio information of each target user;

[0065] It should be noted that, according to the channel state information, the received uplink pilot signal y i (t) Preprocessing, including filtering, downsampling and synchronization processing, eliminating noise and interference signals, and obtaining a preprocessed signal

[0066] It should be noted that the steps for calculating the channel gain and signal-to-noise ratio information are as follows:

[0067] The base station uses the pilot signal to estimate the channel of each user and uses the minimum mean square error algorithm to estimate the channel response h i (t) To estimate:

[0068]

[0069] in, represents the autocorrelation matrix of the received signal, R hy It represents the cross-correlation matrix between the channel response and the received signal. The base station realizes channel estimation through matrix operation.

[0070] It should be noted that the estimated channel response h i (t), calculate the channel gain of each user |h i (t)| 2 :

[0071]

[0072] in, It represents the conjugate of the channel response. The base station calculates the channel gain at each time point t and averages it to obtain a stable channel gain value.

[0073] Based on the received channel response h i (t) and pilot signal y i (t), calculate the signal-to-noise ratio (SNR) of each user i :

[0074]

[0075] Among them, P i represents the transmission power of user i, N0 represents the noise power density, and the base station obtains the value of N0 by measuring the background noise;

[0076] Signal-to-Noise Ratio SNR i Perform time averaging to obtain the average signal-to-noise ratio of each user:

[0077]

[0078] Where T represents the total number of measurement time slots;

[0079] The channel gain and signal-to-noise ratio information of each user is organized into a channel state information set {(|h i (t)| 2 ,SNR avg,i )} and stored in the channel state information database of the base station.

[0080] Based on the grouping algorithm of channel similarity, channel gain and signal-to-noise ratio information, each of the target users is assigned to a group to obtain a plurality of user resource groups, wherein the target users in each user resource group share the same frequency band resources.

[0081] It should be noted that the channel similarity grouping algorithm combines time correlation and spatial domain characteristics. The calculation formula of channel similarity is:

[0082]

[0083] Among them, γ is the weighting coefficient, which adjusts the weight of time correlation and spatial domain features, σ is the standard deviation of channel gain difference, t k represents the kth time point, t0 is the reference time point, λ is the time decay factor, and N is the total number of time points; specifically:

[0084] γ is used to adjust the weight between time correlation and spatial characteristics. Its function is to dynamically adjust the weight of time and space factors in the calculation according to the specific distribution of users and channel status, ensuring that the similarity metric can reflect both the channel characteristics of users that change over time and the relative position distribution of users in the spatial domain. σ is the standard deviation of the channel gain change, reflecting the gain difference between different users. By introducing σ into the metric, the scheme can capture the differences in channel characteristics of users in spatial distribution, so that the similarity calculation not only depends on the average channel gain, but also reflects the impact of user location and environment on the channel, thereby taking into account the differences in user distribution.

[0085] t k (kth time point) and t0 (reference time point): The time point is used to represent the distribution of the channel state on the time axis. By comparing the channel responses at different time points, the scheme can capture the channel changes of users in different time periods, thereby indirectly reflecting the time-varying distribution of users in the network.

[0086] The time decay factor λ controls the exponential decay speed of the time weight, and is used to adjust the influence of the channel similarity that changes over time, so that the channel information weight closer to the reference time point t0 is greater, and the weight farther away gradually decreases. Based on this, it reflects the distribution status of users in the network over time and enhances the attention to the channel status of users at the current moment.

[0087] N represents the number of time samples considered in the similarity measurement, which is related to the temporal distribution breadth of the user. By using information from multiple time points, the scheme can comprehensively analyze the channel performance of the user at multiple time positions and provide a similarity measurement that is more accurate to a certain extent.

[0088] h i (t k ) and h j (tk )(channel gain): represents the time between user i and j at time point t k The channel gain can directly reflect the channel characteristics of users at different locations and time points.

[0089] This application achieves a more comprehensive channel state assessment by incorporating temporal correlation and spatial domain feature considerations into the channel similarity measurement method. Compared with related technologies, this application has the following outstanding advantages:

[0090] Consideration and characterization of time domain and space domain: This method proposes the time attenuation factor λ and the standard deviation σ of the channel gain difference, and combines the time reference point t0 to effectively take into account the evolution of the channel state over time and the characteristics of the space domain. In this way, this application can more accurately reflect the similarity of the channel at different time points, making the grouping decision more in line with the actual channel conditions.

[0091] Weight adjustment mechanism: Based on the adjustable parameter γ, this application can adjust the weights of time correlation and spatial characteristics according to specific application scenarios. This improves the flexibility of the method, enabling it to adaptively adjust the calculation weights when facing different channel environments, thereby maintaining excellent performance under both rapidly changing and stable channel conditions.

[0092] Improved robustness and accuracy: In the calculation of channel similarity, considering the influence of the standard deviation σ and weighting coefficient γ of the channel gain difference helps to filter out the interference of noise and short-term fluctuations on channel similarity. This advantage improves the robustness of the grouping algorithm to different channel states and its sensitivity to real channel changes.

[0093] Smooth transition and stability: The introduction of time correlation, through the exponential decay weight exp(-λ(t k -t0 ensures that channel similarity changes smoothly over time, avoids the impact of sudden changes on the grouping strategy, and ensures the stability of system operation.

[0094] It should be noted that the channel gain h of each user is extracted from the channel state information database. i (t)| 2 and the average signal-to-noise ratio SNR avg,i ; According to the channel similarity matrix calculated by the similarity algorithm, a dynamic user grouping strategy is adopted:

[0095] Set the channel similarity threshold Th. When Sim(i,j)≥Th, assign user i and user j to the same group. Initialize the user group list, traverse all users, and group users according to the channel similarity threshold. After the initial grouping is completed, enter the dynamic adjustment stage. In the dynamic adjustment stage, monitor the changes in user channel status in real time and adjust the user grouping strategy according to the changes, including adding, removing or reallocating users, to ensure the optimality of grouping.

[0096] In the process of user grouping, multi-antenna technology is used for beamforming to improve the signal quality and anti-interference capability of the base station;

[0097] Combine machine learning algorithms to predict and analyze user channel status, adjust user grouping strategies in advance, and reduce the impact of drastic changes in channel status;

[0098]

[0099] Where f is the machine learning model, K is the number of historical time points, and prediction is made using the channel response and signal-to-noise ratio of the past K time points.

[0100] In this application, beamforming is achieved by combining channel state information and multi-antenna technology during the user grouping process. The specific process is described as follows:

[0101] First of all, this application implements user grouping by calculating channel similarity. First, it ensures that users with similar channels are grouped into the same group during grouping, which provides a basis for subsequent beamforming. After the user grouping is completed, the base station uses multi-antenna technology for beamforming. Here, beamforming adjusts the directionality of the antenna array by analyzing the channel information of the users in the group to ensure that the signal strength of the users in the group is maximized while suppressing interference signals. The base station optimizes the weights of the antenna according to the channel gain and spatial characteristics of the user grouping to form a beam focused on the direction of the users in the group. More specifically, during the grouping process, it combines machine learning algorithms to predict changes in user channel states and adjust user grouping and beamforming strategies in advance. Through this mechanism, after grouping, the beamforming can be dynamically optimized according to the actual channel distribution of the user, so that the signal can get better coverage and transmission quality within the group.

[0102] Finally, it is confirmed that the users in the group share the same frequency band resources, and the grouping results are stored in the user grouping database of the base station in the format of G k , G k represents the kth user group.

[0103] Step S30, allocating power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power for each user;

[0104] It should be noted that, within each user group, non-orthogonal multiple access technology is used for power allocation based on the channel gain of each user, and the power allocation algorithm is used to calculate the optimal transmission power of each user to ensure that the signals of users in the group are distinguished by power domain separation at the base station.

[0105] In a feasible implementation manner, the step S30 of allocating power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power of each target user includes:

[0106] Based on the channel gain of each target user in the user resource group, the optimal transmission power of each target user is calculated by a power allocation algorithm to distinguish the transmission signals of the target users in each user resource group.

[0107] It should be noted that the power allocation objective function is defined to maximize the system sum rate or fairness. The power allocation objective function is:

[0108]

[0109] Among them, G k represents the kth user group, P i represents the transmission power of user i, and N0 represents the noise power density;

[0110] The Lagrange multiplier method is used to optimize the power allocation objective function and construct the Lagrangian function:

[0111]

[0112] Among them, λ1 is the Lagrange multiplier, P total is the total power constraint of the user group;

[0113] The Lagrangian function is differentiated and the derivative is set to zero to obtain the optimal transmission power of each user. The solution process is:

[0114]

[0115] The obtained optimal transmit power is substituted into the initial conditions for verification so as to meet the power constraint conditions and the signal-to-noise ratio requirements. The transmit power is adjusted until all the constraints are met to obtain the maximum transmit power.

[0116] The power allocation results within each user group are stored in the power allocation database of the base station and updated in real time to adapt to the dynamic changes in channel status and user needs.

[0117] Step S40: Based on the real-time channel state information and the preset service quality requirement, the user resource grouping and the optimal transmission power are dynamically adjusted to transmit data to each of the users.

[0118] It should be noted that according to the real-time channel status information and the user's service quality requirements, the user grouping and power allocation strategies are dynamically adjusted, and the optimal user grouping and power allocation schemes are recalculated in each time slot using a dynamic optimization algorithm. The system performance is continuously monitored and optimized, and the spectrum efficiency and signal quality of the 5G uplink are improved by periodically updating user channel status information and adjusting the interference management strategy in real time.

[0119] In a feasible implementation manner, the step S40 of dynamically adjusting the user resource grouping and the optimal transmit power based on the real-time channel state information and the preset service quality requirement includes:

[0120] Based on a preset dynamic optimization function, real-time channel state information and preset service quality requirements, the user resource grouping and the optimal transmission power are optimized to obtain an optimization result;

[0121] It should be noted that at the beginning of each time slot, the latest channel state information {(|h i (t)| 2 ,SNR avg,i )} and user's service quality requirements {QoS i};

[0122] It should be noted that the preset dynamic optimization function aims to maximize the spectrum efficiency of the system and meet the service quality requirements of users. The objective function is:

[0123]

[0124] And introduce quality of service constraints:

[0125] QoS i ≥QoS min,i ;

[0126] Among them, QoS min,i is the minimum service quality requirement of user i.

[0127] It should be noted that the user grouping and power allocation are optimized using a dynamic optimization algorithm based on a genetic algorithm. The specific steps include:

[0128] 1. Initialize the population, where each individual in the population represents a possible user grouping and power allocation scheme;

[0129] 2. Calculate the fitness value of each individual in the population. The fitness value is determined by the objective function value and the service quality constraint;

[0130] 3. Perform selection operations based on fitness values, select individuals with high fitness values ​​for crossover and mutation operations, and generate new populations;

[0131] 4. Repeat steps 2 and 3 until the preset number of iterations is reached or the fitness value converges to obtain the optimization result.

[0132] Selecting the best user resource grouping and power allocation strategy from each of the optimization results, and applying the best user resource grouping and power allocation scheme to the current time slot;

[0133] It should be noted that the best user grouping and power allocation scheme is selected from the optimization results and applied to the current time slot.

[0134] The channel state information and the service quality requirements of the target user are monitored in real time. If changes are detected in the channel state information or the service quality requirements, the user resource grouping and power allocation strategy are dynamically adjusted again.

[0135] It should be noted that the channel state information and the user's service quality requirements are monitored in real time. If a significant change in the channel state or service quality requirements is detected, the above resource grouping and power allocation steps are re-executed to dynamically adjust the user grouping and power allocation strategies;

[0136] The user grouping and power allocation results for each time slot are stored in the dynamic optimization database of the base station for subsequent analysis and optimization strategy adjustment.

[0137] The present application proposes an uplink data transmission method, apparatus, device, storage medium and computer program product. The present application obtains channel state information of multiple target users, performs frequency band grouping processing on each target user based on the channel state information, obtains multiple user resource groups, allocates power to each target user according to the channel gain in each user resource group, calculates the optimal transmission power of each target user, and dynamically adjusts the user resource grouping and the optimal transmission power based on real-time channel state information and preset service quality requirements; the dynamic adjustment can improve the flexibility and adaptability of channel data transmission, can quickly respond to changes in channel status and user needs, improve spectrum resource utilization, and optimize system performance and user experience.

[0138] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2, before the step S40 of dynamically adjusting the user resource grouping and the optimal transmit power based on the real-time channel state information and the preset service quality requirements, it also includes steps S300 to S320:

[0139] Step S300, obtaining a mixed signal of each user in the uplink;

[0140] It should be noted that the base station receives the mixed uplink signal y(t), where y(t) is the superposition of multiple user signals:

[0141]

[0142] Among them, h i (t) is the channel response of user i, x i (t) is the transmitted signal of user i, and n(t) is the noise.

[0143] Step S310, based on the interference detection algorithm, the mixed signal is separated and processed to obtain an interference signal and a target signal;

[0144] It should be noted that the signal processing technology is used to detect the interference signals from other users in the uplink in real time, and the interference detection algorithm is used to process the received mixed signal to separate the interference component and the normal signal component.

[0145] Step S320: Based on the interference suppression algorithm, the interference signal is filtered and signal separated to reduce the interference degree of the interference signal on the target signal.

[0146] It should be noted that the interference suppression algorithm is used to suppress the detected interference signal, including adaptive filtering and blind source separation technology, to filter and separate the received signal to reduce the impact of interference on the target user signal.

[0147] In a feasible implementation manner, the step S310 of performing separation processing on the mixed signal based on the interference detection algorithm to obtain the interference signal and the target signal includes:

[0148] Preprocessing the mixed signal to obtain a preprocessed signal;

[0149] It should be noted that the received mixed signal y(t) is preprocessed, and the steps include filtering, noise reduction and signal enhancement to obtain the preprocessed signal

[0150] Analyzing the preprocessed signal by a blind source separation algorithm to obtain an autocorrelation matrix of the mixed signal;

[0151] It should be noted that the improved blind source separation algorithm is used to separate the preprocessed signal Analyze, detect interference signals from other users, and calculate the autocorrelation matrix R of the received signal yy :

[0152] R yy =E[y(t)y H (t)];

[0153] Where E[·] represents the expected value, y H (t) is the conjugate transpose of the received signal.

[0154] In related blind source separation technologies, independent component analysis (ICA) is usually used to process mixed signals, especially the commonly used fast independent component analysis (FastICA) algorithm. The traditional FastICA algorithm maximizes the non-Gaussianity of the signal to separate independent signal sources. Specifically, when processing the received signal, FastICA uses a fixed nonlinear function to estimate the independent components between signal sources, and iteratively calculates a stable separation vector to achieve signal separation.

[0155] This application uses an improved blind source separation algorithm to analyze the autocorrelation matrix to detect and separate interference signals from other users, that is, after obtaining the autocorrelation matrix, the algorithm identifies and separates the interference component by detecting the signal features in the autocorrelation matrix. The improved algorithm can more accurately detect interference signals from other users and further analyze the independence and difference of the signal based on the autocorrelation matrix.

[0156] Iteratively calculating the autocorrelation matrix through a nonlinear function selection mechanism to separate the target signal component and the interference signal component;

[0157] It should be noted that the improved fast independent component analysis algorithm is used to analyze the autocorrelation matrix R yy The innovation lies in the introduction of an adaptive nonlinear function selection mechanism, which adaptively selects the appropriate nonlinear function according to the signal characteristics to optimize the separation performance and computational efficiency. The improved fast independent component analysis algorithm steps are as follows:

[0158]

[0159] Among them, g(·) is the adaptively selected nonlinear function, g'(·) is its derivative, and w (k) is the separation vector of the kth iteration;

[0160] The stable separation vector w is obtained by iterative calculation * Separation of signal components and interference components.

[0161] This application improves the fast independent component analysis algorithm based on the principle of fast independent component analysis (FastICA). The innovation lies in proposing an adaptive nonlinear function selection mechanism to select the most appropriate nonlinear function according to the characteristics of the signal to optimize the separation performance and computational efficiency. By calculating the autocorrelation matrix and combining the improvement of the adaptive nonlinear function, the separation algorithm can better identify the characteristics of different user signals, thereby achieving higher-precision signal separation under complex channel conditions and effectively distinguishing target signals from interference signals.

[0162] From the target signal component and the interference signal component, a signal component whose characteristic value is greater than a first preset threshold is selected as the target signal, and a signal component whose characteristic value is less than a second preset threshold is selected as the interference signal, wherein the first preset threshold is greater than the second preset threshold.

[0163] It should be noted that according to the separation vector w * , decompose the received signal into signal component and interference component, select the component with larger eigenvalue as signal component, and the component with smaller eigenvalue as interference component;

[0164] The received signal is projected through the eigenvector matrix U to obtain the target signal component s(t) and the interference component i(t):

[0165]

[0166] in, is the eigenvector subset of the target signal component, is the eigenvector subset of the interference component;

[0167] The interference component i(t) is further processed by using adaptive filtering technology to adjust the filter parameters according to the real-time channel status. The filter weight update formula is:

[0168] w(n+1)=w(n)+μe(n)x(n);

[0169] Where w(n) is the filter weight of the nth iteration, μ is the adaptive step size, e(n) is the error signal, and x(n) is the input signal;

[0170] The signal characteristics after blind source separation are introduced, and the interference component obtained by blind source separation is used as a reference signal to further improve the effect of interference suppression;

[0171] The purified signal Input to the demodulator for demodulation to ensure high-quality signal reception and processing;

[0172] The results of interference detection and suppression are stored in the interference management database of the base station for subsequent optimization and adjustment.

[0173] In this embodiment, interference detection algorithm and interference suppression algorithm are used for processing. The specific steps include receiving mixed signals, preprocessing signals, blind source separation, separating signals from interference components, further processing interference using adaptive filtering technology, projecting the received signal through a eigenvector matrix, and proposing an improved fast independent component analysis algorithm that can accurately obtain signal components and interference components.

[0174] The beneficial effects of this application are:

[0175] 1. Adopting non-orthogonal multiple access technology, multiple users are allowed to communicate on the same frequency band, and user differentiation is achieved through power domain separation. By optimizing power allocation within each user group, the signals of users in the group are ensured to be differentiated at the base station through power domain separation, thereby improving spectrum utilization and system capacity. Compared with traditional orthogonal multiple access technology, NOMA can support more users to communicate with high quality at the same time, significantly improving the spectrum efficiency and capacity of the 5G system.

[0176] 2. Improved blind source separation algorithm and adaptive filtering technology are used in the base station to effectively detect, suppress and eliminate interference signals from other users in the uplink. By introducing an adaptive nonlinear function selection mechanism, the fast independent component analysis algorithm is improved, the interference separation performance and computational efficiency are improved. In addition, adaptive filtering technology is used to adjust the filter parameters according to the real-time channel status, further improving the interference suppression effect. Through these improvement measures, efficient interference management can be achieved in complex wireless environments, ensuring high-quality signal reception and processing, and improving communication reliability.

[0177] 3. Dynamically adjust user grouping and power allocation strategies based on real-time channel status information and user service quality requirements. A dynamic optimization algorithm based on genetic algorithm is used to recalculate the optimal user grouping and power allocation scheme in each time slot. By initializing the population, calculating the fitness value, selecting operations and crossover mutation, the user grouping and power allocation strategies are optimized to ensure the optimal system performance in a real-time changing wireless environment. Compared with traditional fixed strategies, the dynamic optimization algorithm significantly improves the flexibility and adaptability of the system, can quickly respond to changes in channel status and user needs, and optimize system performance and user experience.

[0178] 4. A number of innovations and improvements have been made in signal processing algorithms. By adopting an improved blind source separation algorithm and adaptive filtering technology, efficient detection and suppression of interference signals are achieved. In addition, the machine learning algorithm is combined to predict and analyze the user channel status, adjust the user grouping strategy in advance, and reduce the impact of drastic changes in channel status, making the interference management of 5G uplink more efficient and reliable in complex wireless environments, significantly improving system performance and user experience.

[0179] For example, to help understand the implementation process of the uplink data transmission method obtained by combining this embodiment with the above-mentioned embodiment 1, please refer to Figure 3 , Figure 3 A schematic diagram of an overall execution flow of an uplink data transmission method is provided, specifically, comprising steps S1 to S7:

[0180] First, through step S1, the channel state information of each target user is obtained, and then channel estimation is performed to obtain the channel gain and signal-to-noise ratio information of each user. In step S2, each user is grouped according to the channel gain and signal-to-noise ratio information so that users in each group share the same frequency band resources; then, through step S3, the power allocation algorithm is used to calculate the optimal transmission power of each user to ensure that the signals of users in the group are distinguished by power domain separation at the base station; step S4, the interference detection algorithm is used to process the received mixed signal and separate the interference component; step S5, the interference suppression algorithm is used to suppress the detected interference signal to reduce the impact of interference on the target user signal. Step S6, using the dynamic optimization algorithm, recalculate the optimal user grouping and power allocation scheme in each time slot; finally, repeat steps S1 to S6 to continuously monitor and optimize system performance, and improve the spectrum efficiency and signal quality of the 5G uplink by periodically updating user channel state information and adjusting the interference management strategy in real time.

[0181] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the uplink data transmission method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0182] This application also provides an uplink data transmission device, please refer to Figure 4 , the uplink data transmission device comprises:

[0183] A first acquisition module 10 is used to acquire channel state information of multiple target users;

[0184] A processing module 20, configured to perform frequency band grouping processing on each target user based on the channel state information to obtain multiple user resource groups;

[0185] The allocation module 30 is used to allocate power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power of each user;

[0186] The adjustment module 40 is used to dynamically adjust the user resource grouping and the optimal transmission power based on real-time channel state information and preset service quality requirements to transmit data to each user.

[0187] Optionally, the processing module includes:

[0188] A determination unit, configured to determine channel gain and signal-to-noise ratio information of each target user based on the channel state information;

[0189] The allocation unit is used to group the target users based on the grouping algorithm of channel similarity, channel gain and signal-to-noise ratio information to obtain multiple user resource groups, wherein the target users in each user resource group share the same frequency band resources.

[0190] Optionally, the allocation module includes:

[0191] The calculation unit is used to calculate the optimal transmission power of each target user through a power allocation algorithm based on the channel gain of each target user in the user resource group, so as to distinguish the transmission signals of the target users in each user resource group.

[0192] Optionally, the adjustment module includes:

[0193] An optimization unit, configured to optimize the user resource grouping and the optimal transmit power based on a preset dynamic optimization function, real-time channel state information, and preset service quality requirements to obtain an optimization result;

[0194] A first selection unit, configured to select an optimal user resource grouping and power allocation strategy from each of the optimization results, and apply the optimal user resource grouping and power allocation scheme to a current time slot;

[0195] The adjustment unit is used to monitor the channel state information and the service quality requirements of the target user in real time, and if it is detected that the channel state information or the service quality requirements have changed, the user resource grouping and power allocation strategy are dynamically adjusted again.

[0196] Optionally, the device further comprises:

[0197] A second acquisition module, used to acquire a mixed signal of each user in the uplink;

[0198] A first separation processing module is used to separate and process the mixed signal based on an interference detection algorithm to obtain an interference signal and a target signal;

[0199] The second separation processing module is used to filter and perform signal separation processing on the interference signal based on an interference suppression algorithm to reduce the interference degree of the interference signal on the target signal.

[0200] Optionally, the first separation processing module includes:

[0201] A preprocessing unit, used for preprocessing the mixed signal to obtain a preprocessed signal;

[0202] An analysis unit, used for analyzing the preprocessed signal by a blind source separation algorithm to obtain an autocorrelation matrix of the mixed signal;

[0203] An iterative calculation unit, used for iteratively calculating the autocorrelation matrix through a nonlinear function selection mechanism to separate the target signal component and the interference signal component;

[0204] The second selection unit is used to select, from the target signal component and the interference signal component, a signal component whose characteristic value is greater than a first preset threshold as a target signal, and select a signal component whose characteristic value is less than a second preset threshold as an interference signal, wherein the first preset threshold is greater than the second preset threshold.

[0205] The uplink data transmission device provided by the present application adopts the uplink data transmission method in the above embodiment to solve the technical problem of uplink data transmission. Compared with the prior art, the beneficial effects of the uplink data transmission device provided by the present application are the same as the beneficial effects of the uplink data transmission method provided by the above embodiment, and other technical features in the uplink data transmission device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0206] The present application provides an uplink data transmission device, which includes: 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 uplink data transmission method in the above-mentioned embodiment one.

[0207] Reference below Figure 5, which shows a schematic diagram of the structure of an uplink data transmission device suitable for implementing the embodiment of the present application. The uplink data transmission device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The uplink data transmission device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0208] like Figure 5 As shown, the uplink data transmission device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the uplink data transmission device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the uplink data transmission device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows an uplink data transmission device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0209] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0210] The uplink data transmission device provided by the present application adopts the uplink data transmission method in the above embodiment to solve the technical problem of uplink data transmission. Compared with the prior art, the beneficial effects of the uplink data transmission device provided by the present application are the same as the beneficial effects of the uplink data transmission method provided by the above embodiment, and other technical features in the uplink data transmission device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0211] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0212] 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.

[0213] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the uplink data transmission method in the above-mentioned embodiment.

[0214] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0215] The computer-readable storage medium may be included in the uplink data transmission device; or may exist independently without being assembled into the uplink data transmission device.

[0216] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the uplink data transmission device, the uplink data transmission device:

[0217] Obtain channel state information of multiple target users;

[0218] Based on the channel state information, frequency band grouping processing is performed on each target user to obtain multiple user resource groups;

[0219] Allocating power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power for each user;

[0220] Based on the real-time channel state information and the preset service quality requirement, the user resource grouping and the optimal transmission power are dynamically adjusted to transmit data to each of the users.

[0221] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0222] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0223] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0224] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned uplink data transmission method, and can solve the technical problems of uplink data transmission. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the uplink data transmission method provided by the above-mentioned embodiment, and will not be repeated here.

[0225] The present application also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the uplink data transmission method as described above are implemented.

[0226] The computer program product provided by the present application can solve the technical problem of uplink data transmission. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the uplink data transmission method provided by the above embodiment, which will not be repeated here.

[0227] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for uplink data transmission, characterized in that: The method comprises: Obtain channel state information of multiple target users; Based on the channel state information, frequency band grouping processing is performed on each target user to obtain multiple user resource groups; Allocating power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power for each user; Based on the real-time channel state information and the preset service quality requirement, the user resource grouping and the optimal transmission power are dynamically adjusted to transmit data to each of the users.

2. The method according to claim 1, characterized in that The step of performing frequency band grouping processing on each target user based on the channel state information to obtain multiple user resource groups includes: Based on the channel state information, determine the channel gain and signal-to-noise ratio information of each target user; Based on the grouping algorithm of channel similarity, channel gain and signal-to-noise ratio information, each of the target users is assigned to a group to obtain a plurality of user resource groups, wherein the target users in each user resource group share the same frequency band resources.

3. The method according to claim 1, characterized in that The step of allocating power to each target user according to the channel gain in each user resource group to obtain the optimal transmission power of each target user includes: Based on the channel gain of each target user in the user resource group, the optimal transmission power of each target user is calculated by a power allocation algorithm to distinguish the transmission signals of the target users in each user resource group.

4. The method according to any one of claims 1 to 3, characterized in that The step of dynamically adjusting the user resource grouping and the optimal transmit power based on the real-time channel state information and the preset service quality requirement includes: Based on a preset dynamic optimization function, real-time channel state information and preset service quality requirements, the user resource grouping and the optimal transmission power are optimized to obtain an optimization result; Selecting the best user resource grouping and power allocation strategy from each of the optimization results, and applying the best user resource grouping and power allocation scheme to the current time slot; The channel state information and the service quality requirements of the target user are monitored in real time. If changes are detected in the channel state information or the service quality requirements, the user resource grouping and power allocation strategy are dynamically adjusted again.

5. The method according to claim 1, characterized in that Before the step of dynamically adjusting the user resource grouping and the optimal transmit power based on the real-time channel state information and the preset service quality requirement, the method further includes: Obtaining mixed signals of each user in the uplink; Based on the interference detection algorithm, the mixed signal is separated and processed to obtain an interference signal and a target signal; Based on the interference suppression algorithm, the interference signal is filtered and signal separated to reduce the interference degree of the interference signal on the target signal.

6. The method according to claim 5, characterized in that The step of separating and processing the mixed signal based on the interference detection algorithm to obtain the interference signal and the target signal includes: Preprocessing the mixed signal to obtain a preprocessed signal; Analyzing the preprocessed signal by a blind source separation algorithm to obtain an autocorrelation matrix of the mixed signal; Iteratively calculating the autocorrelation matrix through a nonlinear function selection mechanism to separate the target signal component and the interference signal component; From the target signal component and the interference signal component, a signal component whose characteristic value is greater than a first preset threshold is selected as the target signal, and a signal component whose characteristic value is less than a second preset threshold is selected as the interference signal, wherein the first preset threshold is greater than the second preset threshold.

7. An uplink data transmission device, characterized in that: The device comprises: A first acquisition module, used to acquire channel state information of multiple target users; A processing module, configured to perform frequency band grouping processing on each target user based on the channel state information to obtain multiple user resource groups; An allocation module, configured to allocate power to each target user according to the channel gain in each user resource group, so as to obtain the optimal transmission power for each user; The adjustment module is used to dynamically adjust the user resource grouping and the optimal transmission power based on real-time channel state information and preset service quality requirements to transmit data to each user.

8. An uplink data transmission device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the uplink data transmission method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the uplink data transmission method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the uplink data transmission method according to any one of claims 1 to 6 are implemented.

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