Method, apparatus and storage medium for determining the selection weights of shaping channels

Abstract

This application provides a method, apparatus, and storage medium for determining the selection weight of a beamforming channel. The method includes: determining a first weight coefficient or a second weight coefficient corresponding to a target beamforming channel based on the reference signal received power parameter in the beamforming channel and a beamforming channel selection weight determination model; the first weight coefficient is the weight coefficient of the target user equipment under the target beamforming channel, and the second weight coefficient is the weight coefficient of all paired user equipments under the target beamforming channel after multi-user pairing is completed; the reference signal received power parameter is the first reference signal received power corresponding to the target user equipment, or the sum of the reference signal received power corresponding to all paired user equipments; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus and storage medium for determining the selection weight of a shaping channel. Background Technology

[0002] To improve the uplink throughput of Massive Multiple Input Multiple Output (MMIMO) New Radio (NR) systems, receiver beamforming processing can be applied to the Physical Uplink Shared Channel (PUSCH).

[0003] After receiving the beamforming signal, the signal energy contained in different beamforming channels is not uniform. Therefore, in traditional schemes, the beamforming channels are selected by measuring the total user's Reference Signal Receiving Power (RSRP) / Received Signal Strength Indication (RSSI) in different beamforming channels and comparing it with a preset threshold in order to improve uplink throughput.

[0004] However, for uplink multi-user multiplexing, when the number of multiplexed users is large and the power is unbalanced among users, the traditional channel selection method will cause significant performance loss for some paired users, especially low-power users. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, embodiments of this application provide a method, apparatus, and storage medium for determining the selection weight of shaping channels.

[0006] In a first aspect, embodiments of this application provide a method for determining the weight of shaping channel selection, including:

[0007] Based on the reference signal received power parameters in the beamforming channel and the beamforming channel selection weight determination model, the first weight coefficient or the second weight coefficient corresponding to the target beamforming channel is determined; the first weight coefficient is the weight coefficient of the target user equipment under the target beamforming channel, and the second weight coefficient is the weight coefficient of all paired user equipments under the target beamforming channel after multi-user pairing is completed;

[0008] The reference signal received power parameter is either the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipment, wherein the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipment; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

[0009] Optionally, the shaping channel selection weight determination model is determined based on the following steps:

[0010] Obtain the channel capacity function under the MIMO channel with the power allocation factor of the shaping channel, the received power parameter of the reference signal, and the noise power of the shaping channel as independent variables;

[0011] The problem of maximizing channel capacity is defined and transformed into a convex optimization problem. The Lagrangian function is introduced to determine the optimal solution of the weight coefficients of the shaping channel under the conditions of satisfying the Kuhn-Tak condition and the average allocation constraint, and the shaping channel selection weight determination model is determined.

[0012] Optionally, the first weighting coefficient satisfies:

[0013]

[0014] in, σ represents the first weighting coefficient of the j-th user equipment in the i-th shaped channel, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 This represents the average noise power of all shaped channels before channel selection. This represents the reference signal received power of the j-th user equipment in the i-th shaped channel.

[0015] Optionally, it also includes:

[0016] The uplink signal power of the target beamforming channel is determined based on the sum of the products of the first reference signal received power corresponding to all user equipment in the target beamforming channel and the first weighting coefficient of all user equipment in the target beamforming channel.

[0017] Optionally, the uplink signal power of the target beamforming channel is determined by the following calculation formula:

[0018]

[0019] in, Let represent the uplink signal power of the i-th shaped channel out of Nr shaped channels. This represents the first weighting coefficient of the j-th user equipment in the i-th beamforming channel. N represents the reference signal received power of the j-th user in the ith shaped channel. UE This indicates the number of target user devices.

[0020] Optionally, the second weighting coefficient satisfies:

[0021]

[0022] Where, α i σ represents the second weighting coefficient of all paired user equipment under i shaped channels, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 Rsrp represents the average noise power of all shaped channels before channel selection. i This represents the sum of the reference signal received power of all paired user equipment in the i-th shaped channel.

[0023] Optionally, it also includes:

[0024] The uplink signal power of the target shaping channel is determined based on the product of the second reference signal received power and the second weighting coefficient.

[0025] Optionally, the uplink signal power of the target beamforming channel is determined by the following calculation formula:

[0026]

[0027] in, α represents the uplink signal power of the i-th shaped channel out of Nr shaped channels. i This represents the second weighting coefficient of all paired user equipment in the i-th shaping channel. N represents the reference signal received power of the j-th paired user equipment in the i-th shaped channel. UE This indicates the number of paired user devices.

[0028] Optionally, after determining the uplink signal power of the target shaping channel, the method further includes:

[0029] The shaping channels are sorted in descending order based on the uplink signal power to determine a preset number of shaping channels.

[0030] Secondly, embodiments of this application also provide an electronic device, including a memory, a transceiver, and a processor, wherein:

[0031] A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs in the memory and implementing the steps of the shaping channel selection weight determination method as described in the first aspect above.

[0032] Thirdly, embodiments of this application also provide a shaping channel selection weight determination device, comprising:

[0033] The first determining unit is used to determine a first weighting coefficient or a second weighting coefficient corresponding to the target beamforming channel based on the reference signal received power parameters in the beamforming channel and the beamforming channel selection weighting determination model; the first weighting coefficient is the weighting coefficient of the target user equipment under the target beamforming channel, and the second weighting coefficient is the weighting coefficient of all paired user equipments under the target beamforming channel after multi-user pairing is completed.

[0034] The reference signal received power parameter is either the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipment, wherein the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipment; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

[0035] Fourthly, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing the processor to perform the steps of the shaping channel selection weight determination method described in the first aspect above.

[0036] Fifthly, embodiments of this application also provide a computer-readable storage medium storing a computer program for causing a computer to perform the steps of the shaping channel selection weight determination method provided in the first aspect as described above.

[0037] In a sixth aspect, embodiments of this application also provide a communication device readable storage medium storing a computer program for causing the communication device to perform the steps of the shaping channel selection weight determination method provided in the first aspect as described above.

[0038] In a seventh aspect, embodiments of this application also provide a chip product readable storage medium storing a computer program for causing the chip product to perform the steps of the shaping channel selection weight determination method provided in the first aspect as described above.

[0039] The beamforming channel selection weight determination method, apparatus, and storage medium provided in this application embodiment determine the weight coefficients based on the channel capacity function of the MIMO system, with the optimization objective of maximizing channel capacity, the constraint of the Kuntak condition, and the constraint of the average allocation principle. The weight coefficients are determined by combining nonlinear and linear methods, thereby determining the weight coefficients of different user equipment under different beamforming channels or the weight coefficients of all paired user equipment under different beamforming channels, thus correcting the uplink throughput loss caused by power imbalance between users. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart illustrating the existing technology for shaping channel selection based on received data.

[0042] Figure 2 This is a flowchart illustrating the existing beamforming channel selection method based on channel estimation.

[0043] Figure 3 This is a flowchart illustrating the method for determining the shaping channel selection weights provided in an embodiment of this application.

[0044] Figure 4 This is one of the flowcharts illustrating the shaping channel selection method provided in the embodiments of this application;

[0045] Figure 5 This is a second schematic flowchart of the shaping channel selection method provided in the embodiments of this application;

[0046] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application;

[0047] Figure 7 This is a schematic diagram of the structure of the shaping channel selection weight determination device provided in the embodiments of this application. Detailed Implementation

[0048] To better describe the technical solutions in the embodiments of this application, relevant knowledge is introduced below.

[0049] (1) Channel capacity

[0050] Under MIMO, the channel capacity is expressed as follows:

[0051]

[0052] Where C represents the channel capacity, N r N represents the number of receive channels. t Indicates the number of transmission channels. N represents r An identity matrix of dimensions Indicates the power allocation factor. Denotes the channel estimation matrix, σ 2 This indicates the noise power of the receiving channel, with the superscript H indicating conjugate transpose. In the embodiments of this application, the shaping channel mainly refers to the receiving channel.

[0053] The above formula can be transformed into:

[0054]

[0055] Where, N UE Indicates the number of User Equipment (UE). This indicates the number of ports per UE.

[0056] because It is the channel estimation matrix after beamforming and before channel selection, obtained through N r It is derived from the orthogonal codebook, therefore... Singular Value Decomposition (SVD) is performed, satisfying the following calculation formula:

[0057]

[0058] Where U represents N r *N r A unitary matrix of dimension V, representing A unitary matrix of dimension 1. and

[0059] Therefore, the modified channel capacity formula can be simplified to:

[0060]

[0061] Among them, K i This represents the power allocation factor for the i-th shading channel. σ represents the signal power of the i-th shaping channel. 2 SNR represents the average noise power of all shaped channels. i This represents the signal-to-noise ratio of the i-th shaping channel.

[0062] (2) PUSCH channel selection

[0063] Figure 1 This is a flowchart illustrating a prior art method for selecting a beamforming channel based on received data. Figure 2 This is a flowchart illustrating the existing beamforming channel selection method based on channel estimation, as shown below. Figure 1 and Figure 2 As shown, to improve the uplink throughput of Massive MIMO NR systems, the mainstream technology currently involves receiving beamforming of the PUSCH channel, including beamforming methods based on received data and beamforming methods based on channel estimation. Here, SRS stands for Sounding Reference Signal.

[0064] After receiving and shaping, the signal energy of users in different receiving channels is not uniform. Therefore, the existing technology determines the receiving channel selection by measuring the RSRP / RSSI of the total number of users in different receiving channels and comparing it with a preset threshold. Although this can significantly improve uplink throughput, it results in a large loss of uplink throughput when there is multiple uplink users and power imbalance among users, especially causing a large performance loss for low-power users.

[0065] To address the aforementioned problems in the existing technology, this application provides a method, apparatus, and storage medium for determining the weights of beamforming channel selection. Based on the channel capacity function of the MIMO system, the method aims to maximize channel capacity, constrained by the Kuhn-Tak condition and the principle of average allocation, and determines the weight coefficients using a combination of nonlinear and linear methods. This determines the weight coefficients of different user equipment under different beamforming channels or the weight coefficients of all paired user equipment under different beamforming channels, thereby correcting the uplink throughput loss caused by power imbalance among users.

[0066] In this application's embodiments, the character " / " generally indicates that the preceding and following objects have an "or" relationship. In this application's embodiments, the term "multiple" refers to two or more, and other quantifiers are similar.

[0067] The technical solutions provided in this application can be applied to various systems, especially 5G systems. For example, applicable systems include Global System for Mobile Communication (GSM), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA) General Packet Radio Service (GPRS), Long Term Evolution (LTE), LTE Frequency Division Duplex (FDD), LTE Time Division Duplex (TDD), Long Term Evolution Advanced (LTE-A), Universal Mobile Telecommunication System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX), and 5G New Radio (NR). All of these systems include terminal equipment and network equipment. The system may also include a core network component, such as the Evolved Packet System (EPS) or the 5G system (5GS).

[0068] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0069] Figure 3 This is a flowchart illustrating the method for determining the shaping channel selection weights provided in an embodiment of this application, as shown below. Figure 3 As shown, the method includes at least the following steps:

[0070] Step 301: Based on the reference signal received power parameter in the beamforming channel and the beamforming channel selection weight determination model, determine the first weight coefficient or the second weight coefficient corresponding to the target beamforming channel; the first weight coefficient is the weight coefficient of the target user equipment under the target beamforming channel, and the second weight coefficient is the weight coefficient of all paired user equipments under the target beamforming channel after multi-user pairing is completed; the reference signal received power parameter is the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipments, and the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipments; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and taking the Kuhn-Tak condition and the average allocation constraint as constraints.

[0071] Specifically, for NR systems, there is a strong correlation between theoretical throughput and channel capacity. Therefore, the optimization of the channel selection algorithm during the uplink PUSCH channel receive shaping process needs to maximize the preservation of the MIMO system's channel capacity.

[0072] After obtaining the reference signal received power parameters in the beamforming channel, the weight coefficients corresponding to the target beamforming channel can be determined based on the reference signal received power parameters in the beamforming channel and the pre-established beamforming channel selection weight determination model.

[0073] In this embodiment, the beamforming channel selection weight determination method is divided into two cases: user-specific and user-merged. In the user-specific case, the reference signal received power parameter is the first reference signal received power corresponding to the target user equipment, and the target user equipment is any user equipment in the beamforming channel. The first weight coefficient of the target user equipment in the target beamforming channel is calculated using the RSRP corresponding to the target user equipment and the pre-established beamforming channel selection weight determination model.

[0074] Second, user merging: After multi-user (MU) pairing is completed, the reference signal received power parameter is the sum of the reference signal received power corresponding to all paired user equipment. In this embodiment, the second reference signal received power refers to the sum of the reference signal received power corresponding to all paired user equipment. The second weight coefficient of all paired user equipment under the target beamforming channel is calculated using the sum of the RSRP corresponding to all paired user equipment and the pre-established beamforming channel selection weight determination model.

[0075] The beamforming channel selection weight determination model aims to maximize the channel capacity of a MIMO channel, using the Kuhn-Tak condition and average allocation constraint as constraints to jointly optimize the weight coefficients. By using the Kuhn-Tak condition and average allocation constraint as constraints, the weight coefficients for RSRP can be calculated simultaneously using both nonlinear and linear methods, thus reducing the selection weight of high-power users and increasing the selection weight of low-power users in the channel selection process.

[0076] Therefore, using the weight coefficients obtained from the optimization calculation of the beamforming channel selection weight determination model to select the beamforming channel can maximize the channel capacity, while correcting the uplink throughput loss caused by the power imbalance between users and improving the system's uplink throughput.

[0077] Optionally, the shaping channel selection weight determination model is determined based on the following steps:

[0078] Obtain the channel capacity function under the MIMO channel with the power allocation factor of the shaping channel, the received power parameter of the reference signal, and the noise power of the shaping channel as independent variables;

[0079] The problem of maximizing channel capacity is defined and transformed into a convex optimization problem. The Lagrangian function is introduced to determine the optimal solution of the weight coefficients of the shaping channel under the conditions of satisfying the Kuhn-Tak condition and the average allocation constraint, and the shaping channel selection weight determination model is determined.

[0080] Specifically, the process of establishing the model for determining the weights of shaping channels includes:

[0081] Obtain the channel capacity function under MIMO channel with the power allocation factor of the shaping channel, the received power parameter of the reference signal, and the noise power of the shaping channel as independent variables.

[0082] For the case of merged users, the expression for the channel capacity function is:

[0083]

[0084] Where C represents the channel capacity, N r K represents the number of shaping channels. i Rsrp represents the power allocation factor of the i-th shaped channel. i σ represents the sum of the reference signal received power of all paired user equipment in the i-th shaped channel. 2 This represents the average noise power of all shaped channels before channel selection.

[0085] Under the premise of maximizing channel capacity, the uplink reception criterion can be transformed into:

[0086]

[0087] And α i ≥0, i=1,2,…,N r

[0088] Where, α i This represents the second weighting coefficient for all paired user equipment across i shaping channels. `st` is an abbreviation for "subject to," meaning subject to constraints.

[0089] The problem of maximizing channel capacity is defined and transformed into a convex optimization problem. According to the theory of convex optimization for planning problems, the above formula can be transformed into a Lagrangian function:

[0090]

[0091] The formula requires the Kuhn-Tucker Conditions to reach its extreme value, namely:

[0092]

[0093] Further deformation yields:

[0094]

[0095] According to the principle of equal distribution, we can obtain:

[0096]

[0097] Further deformation yields:

[0098]

[0099] Finally, the second weighting coefficients of all paired user equipment under the target beamforming channel are obtained, satisfying the following:

[0100]

[0101] Where, α i σ represents the second weighting coefficient of all paired user equipment under i shaped channels, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 Rsrp represents the average noise power of all shaped channels before channel selection. i This represents the sum of the reference signal received power of all paired user equipment in the i-th shaped channel.

[0102] For the case of user-specific applications, based on the same derivation process, the first weighting coefficient of the target user device under the target beamforming channel can be obtained as follows:

[0103]

[0104] in, σ represents the first weighting coefficient of the j-th user equipment in the i-th shaped channel, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 This represents the average noise power of all shaped channels before channel selection. This represents the reference signal received power of the j-th user equipment in the i-th shaped channel.

[0105] The beamforming channel selection weight determination method provided in this application determines the weight coefficients based on the channel capacity function of the MIMO system, with the optimization objective of maximizing channel capacity, the constraint of the Kuntak condition, and the constraint of the average allocation principle. It combines nonlinear and linear methods to determine the weight coefficients of different user equipment under different beamforming channels or the weight coefficients of all paired user equipment under different beamforming channels, thereby correcting the uplink throughput loss caused by power imbalance between users.

[0106] Optionally, it also includes:

[0107] The uplink signal power of the target beamforming channel is determined based on the sum of the products of the first reference signal received power corresponding to all user equipment in the target beamforming channel and the first weighting coefficient of all user equipment in the target beamforming channel.

[0108] Specifically, for the user-specific case, the uplink signal power of the target shaped channel is obtained by summing the products of the first reference signal received power corresponding to all user equipment in the target shaped channel and the first weighting coefficient of all user equipment in the target shaped channel. In this embodiment, the uplink signal power of the target shaped channel is referred to as pseudo power, which is obtained by weighting the original RSRP value.

[0109] Optionally, the uplink signal power of the target shaping channel is determined to satisfy the following calculation formula:

[0110]

[0111] in, Let represent the uplink signal power of the i-th shaped channel out of Nr shaped channels. This represents the first weighting coefficient of the j-th user equipment in the i-th beamforming channel. N represents the reference signal received power of the j-th user in the ith shaped channel. UE This indicates the number of target user devices.

[0112] Optionally, after determining the uplink signal power of the target shaping channel, the method further includes:

[0113] The shaping channels are sorted in descending order based on the uplink signal power to determine a preset number of shaping channels.

[0114] Specifically, when the uplink signal power of the target shaping channel is obtained After that, The channels are sorted in descending order, and the channel numbers or index numbers of the top N shaping channels are selected and sent to the channel selection function module of the PUSCH signal for processing. The preset number N can be selected according to the actual situation.

[0115] Alternatively, when the uplink signal power of the target shaping channel is obtained. Next, select The corresponding shaping channel number or index number is sent to the channel selection function module of the PUSCH signal for processing.

[0116] The beamforming channel selection weight determination method provided in this application obtains the weight coefficients of different user equipment under different beamforming channels, and determines the weighted uplink signal power of different beamforming channels based on the weight coefficients of different user equipment under different beamforming channels and the reference signal received power of different user equipment under different beamforming channels. Thus, the beamforming channel is selected according to the weighted uplink signal power, which reduces the system performance loss caused by the power imbalance between users in the traditional channel selection process.

[0117] Optionally, it also includes:

[0118] The uplink signal power of the target shaping channel is determined based on the product of the second reference signal received power and the second weighting coefficient.

[0119] Specifically, for the case of merged users, the uplink signal power of the target beamforming channel is obtained based on the sum of the reference signal received power of all paired user equipment and the second weighting coefficient of all paired user equipment under the target beamforming channel.

[0120] Optionally, the uplink signal power of the target beamforming channel is determined by the following calculation formula:

[0121]

[0122] in, α represents the uplink signal power of the i-th shaped channel out of Nr shaped channels. i This represents the second weighting coefficient of all paired user equipment in the i-th shaping channel. N represents the reference signal received power of the j-th paired user equipment in the i-th shaped channel. UE This indicates the number of paired user devices.

[0123] Specifically, after multi-user pairing is completed, the number of paired user devices is the same as the total number of user devices in the shaping channel.

[0124] Optionally, after determining the uplink signal power of the target shaping channel, the method further includes:

[0125] The shaping channels are sorted in descending order based on the uplink signal power to determine a preset number of shaping channels.

[0126] Specifically, when the uplink signal power of the target shaping channel is obtained After that, The channels are sorted in descending order, and the channel numbers or index numbers of the top N shaping channels are selected and sent to the channel selection function module of the PUSCH signal for processing. The preset number N can be selected according to the actual situation.

[0127] Alternatively, when the uplink signal power of the target shaping channel is obtained. Next, select The corresponding shaping channel number or index number is sent to the channel selection function module of the PUSCH signal for processing.

[0128] The beamforming channel selection weight determination method provided in this application obtains the weight coefficients of all paired user equipment under different beamforming channels, and then determines the weighted uplink signal power of different beamforming channels based on the weight coefficients of all paired user equipment under different beamforming channels and the sum of the reference signal received power of all paired user equipment under different beamforming channels. Thus, the beamforming channel is selected according to the weighted uplink signal power, reducing the system performance loss caused by the power imbalance between users in the traditional channel selection process.

[0129] The beamforming weight determination method provided in this application embodiment is illustrated below with a specific example:

[0130] Figure 4 This is one of the flowcharts illustrating the shaping channel selection method provided in the embodiments of this application. Figure 5 This is a second schematic flowchart of the shaping channel selection method provided in the embodiments of this application, such as... Figure 4 and Figure 5 As shown, compared with the shaping channel selection method in the prior art, the embodiments of this application add the steps of generating channel weight coefficients and pseudo RSRP sorting / channel index selection.

[0131] Among them, the generation of channel weight coefficients can be divided into two methods: separate user and merged user.

[0132] For Method 1: User-based. The expression for the weighting coefficients of different user devices under different beamforming channels is as follows:

[0133]

[0134] in, σ represents the weighting coefficient of the j-th user equipment in the i-th shaped channel, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the weighting coefficient of the j-th user equipment in the i-th shaped channel. 2 This represents the average noise power of all shaped channels before channel selection. This represents the reference signal received power of the j-th user equipment in the i-th shaped channel.

[0135] The pseudo RSRP for each beamforming channel is obtained based on the weighting coefficients of different user devices under different beamforming channels:

[0136]

[0137] in, Let represent the uplink signal power of the i-th shaped channel out of Nr shaped channels. This represents the first weighting coefficient of the j-th user equipment in the i-th beamforming channel. N represents the reference signal received power of the j-th user in the ith shaped channel. UE This indicates the number of target user devices.

[0138] For Method Two: Merging Users. After multi-user pairing is completed, the expression for the weighting coefficients of all paired user devices under different beamforming channels is:

[0139]

[0140] Where, α i σ represents the second weighting coefficient for all paired user equipment under i shaped channels, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 Rsrp represents the average noise power of all shaped channels before channel selection. i This represents the sum of the reference signal received power of all paired user equipment in the i-th shaped channel.

[0141] Based on the weighting coefficients of all paired user equipment in different shaped channels and the sum of the reference signal received power of all paired users in different shaped channels, obtain the pseudo RSRP for each shaped channel:

[0142]

[0143] in, α represents the uplink signal power of the i-th shaped channel out of Nr shaped channels. i This represents the second weighting coefficient for all paired user equipment in the i-th shaping channel. N represents the reference signal received power of the j-th paired user equipment in the i-th shaped channel. UE This indicates the number of paired user devices.

[0144] The pseudo-RSRP sorting / channel index selection step specifically includes:

[0145] ① Fixed channel number selection: For pseudo RSRP, i.e. The channels are sorted in descending order, and the channel numbers or index numbers of the top N shaping channels are selected and sent to the channel selection function module of the PUSCH signal for processing.

[0146] ② Adaptive Channel Quantity Selection: Select pseudo RSRP, i.e. The channel number or index number of the shaping channel corresponding to a value greater than 0 is sent to the channel selection function module of the PUSCH signal for processing.

[0147] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application, such as... Figure 6 As shown, the electronic device may include: a processor 601, a communications interface 602, a memory 603, and a communication bus 604, wherein the processor 601, the communications interface 602, and the memory 603 communicate with each other via the communication bus 604. The processor 601 can call a computer program stored in the memory 603 and executable on the processor 601 to perform the following steps:

[0148] Processor 601 is configured to read the computer program in the memory 603 and perform the following operations:

[0149] Based on the reference signal received power parameters in the beamforming channel and the beamforming channel selection weight determination model, the first weight coefficient or the second weight coefficient corresponding to the target beamforming channel is determined; the first weight coefficient is the weight coefficient of the target user equipment under the target beamforming channel, and the second weight coefficient is the weight coefficient of all paired user equipments under the target beamforming channel after multi-user pairing is completed;

[0150] The reference signal received power parameter is either the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipment, wherein the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipment; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

[0151] Optionally, the shaping channel selection weight determination model is determined based on the following steps:

[0152] Obtain the channel capacity function under the MIMO channel with the power allocation factor of the shaping channel, the received power parameter of the reference signal, and the noise power of the shaping channel as independent variables;

[0153] The problem of maximizing channel capacity is defined and transformed into a convex optimization problem. The Lagrangian function is introduced to determine the optimal solution of the weight coefficients of the shaping channel under the conditions of satisfying the Kuhn-Tak condition and the average allocation constraint, and the shaping channel selection weight determination model is determined.

[0154] Optionally, the first weighting coefficient satisfies:

[0155]

[0156] in, σ represents the first weighting coefficient of the j-th user equipment in the i-th shaped channel, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 This represents the average noise power of all shaped channels before channel selection. This represents the reference signal received power of the j-th user equipment in the i-th shaped channel.

[0157] Optionally, it also includes:

[0158] The uplink signal power of the target beamforming channel is determined based on the sum of the products of the first reference signal received power corresponding to all user equipment in the target beamforming channel and the first weighting coefficient of all user equipment in the target beamforming channel.

[0159] Optionally, the uplink signal power of the target beamforming channel is determined by the following calculation formula:

[0160]

[0161] in, Let represent the uplink signal power of the i-th shaped channel out of Nr shaped channels. This represents the first weighting coefficient of the j-th user equipment in the i-th beamforming channel. N represents the reference signal received power of the j-th user in the ith shaped channel. UE This indicates the number of target user devices.

[0162] Optionally, the second weighting coefficient satisfies:

[0163]

[0164] Where, α i σ represents the second weighting coefficient of all paired user equipment under i shaped channels, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 Rsrp represents the average noise power of all shaped channels before channel selection. i This represents the sum of the reference signal received power of all paired user equipment in the i-th shaped channel.

[0165] Optionally, the operation further includes:

[0166] The uplink signal power of the target shaping channel is determined based on the product of the second reference signal received power and the second weighting coefficient.

[0167] Optionally, the uplink signal power of the target beamforming channel is determined by the following calculation formula:

[0168]

[0169] in, α represents the uplink signal power of the i-th shaped channel out of Nr shaped channels. i This represents the second weighting coefficient of all paired user equipment in the i-th shaping channel. N represents the reference signal received power of the j-th paired user equipment in the i-th shaped channel. UE This indicates the number of paired user devices.

[0170] Optionally, after determining the uplink signal power of the target shaping channel, the method further includes:

[0171] The shaping channels are sorted in descending order based on the uplink signal power to determine a preset number of shaping channels.

[0172] It should be noted that the electronic device provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiment and achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0173] Figure 7 This is a schematic diagram of the structure of the shaping channel selection weight determination device provided in the embodiments of this application, as shown below. Figure 7 As shown, the device includes:

[0174] The first determining unit 701 is used to determine a first weighting coefficient or a second weighting coefficient corresponding to the target beamforming channel based on the reference signal received power parameters in the beamforming channel and the beamforming channel selection weighting determination model; the first weighting coefficient is the weighting coefficient of the target user equipment under the target beamforming channel, and the second weighting coefficient is the weighting coefficient of all paired user equipments under the target beamforming channel after multi-user pairing is completed.

[0175] The reference signal received power parameter is either the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipment, wherein the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipment; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

[0176] Optionally, the shaping channel selection weight determination model is determined based on the following steps:

[0177] Obtain the channel capacity function under the MIMO channel with the power allocation factor of the shaping channel, the received power parameter of the reference signal, and the noise power of the shaping channel as independent variables;

[0178] The problem of maximizing channel capacity is defined and transformed into a convex optimization problem. The Lagrangian function is introduced to determine the optimal solution of the weight coefficients of the shaping channel under the conditions of satisfying the Kuhn-Tak condition and the average allocation constraint, and the shaping channel selection weight determination model is determined.

[0179] Optionally, the first weighting coefficient satisfies:

[0180]

[0181] in, σ represents the first weighting coefficient of the j-th user equipment in the i-th shaped channel, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 This represents the average noise power of all shaped channels before channel selection. This represents the reference signal received power of the j-th user equipment in the i-th shaped channel.

[0182] Optionally, the device further includes:

[0183] The second determining unit is used to determine the uplink signal power of the target beamforming channel based on the sum of the products of the first reference signal received power corresponding to all user equipment in the target beamforming channel and the first weighting coefficient of all user equipment in the target beamforming channel.

[0184] Optionally, the uplink signal power of the target beamforming channel is determined by the following calculation formula:

[0185]

[0186] in, Let represent the uplink signal power of the i-th shaped channel out of Nr shaped channels. This represents the first weighting coefficient of the j-th user equipment in the i-th beamforming channel. N represents the reference signal received power of the j-th user in the ith shaped channel. UE This indicates the number of target user devices.

[0187] Optionally, the second weighting coefficient satisfies:

[0188]

[0189] Where, α i σ represents the second weighting coefficient of all paired user equipment under i shaped channels, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 Rsrp represents the average noise power of all shaped channels before channel selection. i This represents the sum of the reference signal received power of all paired user equipment in the i-th shaped channel.

[0190] Optionally, the device further includes:

[0191] The third determining unit is used to determine the uplink signal power of the target shaping channel based on the product of the second reference signal received power and the second weighting coefficient.

[0192] Optionally, the uplink signal power of the target beamforming channel is determined by the following calculation formula:

[0193]

[0194] in, α represents the uplink signal power of the i-th shaped channel out of Nr shaped channels. i This represents the second weighting coefficient of all paired user equipment in the i-th shaping channel. N represents the reference signal received power of the j-th paired user equipment in the i-th shaped channel. UEThis indicates the number of paired user devices.

[0195] Optionally, the device further includes:

[0196] The fourth determining unit is used to sort the shaping channels in descending order based on the uplink signal power and determine a preset number of shaping channels.

[0197] The methods and apparatuses provided in the various embodiments of this application are based on the same concept. Since the methods and apparatuses solve problems in similar ways, the implementations of the apparatuses and methods can refer to each other, and repeated details will not be repeated.

[0198] It should be noted that the division of units in the embodiments of this application is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units.

[0199] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0200] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0201] On the other hand, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing the processor to execute the shaping channel selection weight determination method provided in the above embodiments, for example, including:

[0202] Based on the reference signal received power parameters in the beamforming channel and the beamforming channel selection weight determination model, the first weight coefficient or the second weight coefficient corresponding to the target beamforming channel is determined; the first weight coefficient is the weight coefficient of the target user equipment under the target beamforming channel, and the second weight coefficient is the weight coefficient of all paired user equipments under the target beamforming channel after multi-user pairing is completed;

[0203] The reference signal received power parameter is either the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipment, wherein the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipment; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

[0204] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0205] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0206] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0207] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0208] These processors can execute instructions that can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0209] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for determining the selection weight of shaping channels, characterized in that, include: Based on the reference signal received power parameters in the beamforming channel and the beamforming channel selection weight determination model, determine the first weight coefficient or the second weight coefficient corresponding to the target beamforming channel; The first weighting coefficient is the weighting coefficient of the target user equipment under the target beamforming channel, and the second weighting coefficient is the weighting coefficient of all paired user equipment under the target beamforming channel after multi-user pairing is completed; The reference signal received power parameter is either the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipment, wherein the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipment; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

2. The method for determining the selection weight of shaping channels according to claim 1, characterized in that, The shaping channel selection weight determination model is based on the following steps: Obtain the channel capacity function under the MIMO channel with the power allocation factor of the shaping channel, the received power parameter of the reference signal, and the noise power of the shaping channel as independent variables; The problem of maximizing channel capacity is defined and transformed into a convex optimization problem. The Lagrangian function is introduced to determine the optimal solution of the weight coefficients of the shaping channel under the conditions of satisfying the Kuhn-Tak condition and the average allocation constraint, and the shaping channel selection weight determination model is determined.

3. The method for determining the selection weight of shaping channels according to claim 2, characterized in that, The first weighting coefficient satisfies: in, σ represents the first weighting coefficient of the j-th user equipment in the i-th shaped channel, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 This represents the average noise power of all shaped channels before channel selection. This represents the reference signal received power of the j-th user equipment in the i-th shaped channel.

4. The method for determining the selection weight of shaping channels according to claim 3, characterized in that, Also includes: The uplink signal power of the target beamforming channel is determined based on the sum of the products of the first reference signal received power corresponding to all user equipment in the target beamforming channel and the first weighting coefficient of all user equipment in the target beamforming channel.

5. The method for determining the selection weight of shaping channels according to claim 4, characterized in that, The uplink signal power of the target shaping channel is determined by the following calculation formula: in, Let represent the uplink signal power of the i-th shaped channel out of Nr shaped channels. This represents the first weighting coefficient of the j-th user equipment in the i-th beamforming channel. N represents the reference signal received power of the j-th user in the ith shaped channel. UE This indicates the number of target user devices.

6. The method for determining the selection weight of shaping channels according to claim 2, characterized in that, The second weighting coefficient satisfies: Where, α i σ represents the second weighting coefficient of all paired user equipment under i shaped channels, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 Rsrp represents the average noise power of all shaped channels before channel selection. i This represents the sum of the reference signal received power of all paired user equipment in the i-th shaped channel.

7. The method for determining the selection weight of shaping channels according to claim 6, characterized in that, Also includes: The uplink signal power of the target shaping channel is determined based on the product of the second reference signal received power and the second weighting coefficient.

8. The method for determining the selection weight of shaping channels according to claim 7, characterized in that, The uplink signal power of the target shaping channel is determined by the following calculation formula: in, α represents the uplink signal power of the i-th shaped channel out of Nr shaped channels. i This represents the second weighting coefficient of all paired user equipment in the i-th shaping channel. N represents the reference signal received power of the j-th paired user equipment in the i-th shaped channel. UE This indicates the number of paired user devices.

9. The method for determining the shaping channel selection weights according to any one of claims 4 or 7, characterized in that, After determining the uplink signal power of the target shaping channel, the method further includes: The shaping channels are sorted in descending order based on the uplink signal power to determine a preset number of shaping channels.

10. An electronic device, comprising a memory, a transceiver, and a processor; characterized in that: A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs from the memory and performing the following operations: Based on the reference signal received power parameters in the beamforming channel and the beamforming channel selection weight determination model, the first weight coefficient or the second weight coefficient corresponding to the target beamforming channel is determined; the first weight coefficient is the weight coefficient of the target user equipment under the target beamforming channel, and the second weight coefficient is the weight coefficient of all paired user equipment under the target beamforming channel after multi-user pairing is completed; The reference signal received power parameter is either the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipment, wherein the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipment; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

11. The electronic device according to claim 10, characterized in that, The shaping channel selection weight determination model is based on the following steps: Obtain the channel capacity function under the MIMO channel with the power allocation factor of the shaping channel, the received power parameter of the reference signal, and the noise power of the shaping channel as independent variables; The problem of maximizing channel capacity is defined and transformed into a convex optimization problem. The Lagrangian function is introduced to determine the optimal solution of the weight coefficients of the shaping channel under the conditions of satisfying the Kuhn-Tak condition and the average allocation constraint, and the shaping channel selection weight determination model is determined.

12. The electronic device according to claim 11, characterized in that, The first weighting coefficient satisfies: in, σ represents the first weighting coefficient of the j-th user equipment in the i-th shaped channel, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 This represents the average noise power of all shaped channels before channel selection. This represents the reference signal received power of the j-th user equipment in the i-th shaped channel.

13. The electronic device according to claim 12, characterized in that, The operation also includes: The uplink signal power of the target beamforming channel is determined based on the sum of the products of the first reference signal received power corresponding to all user equipment in the target beamforming channel and the first weighting coefficient of all user equipment in the target beamforming channel.

14. The electronic device according to claim 13, characterized in that, The uplink signal power of the target shaping channel is determined by the following calculation formula: in, Let represent the uplink signal power of the i-th shaped channel out of Nr shaped channels. This represents the first weighting coefficient of the j-th user equipment in the i-th beamforming channel. N represents the reference signal received power of the j-th user in the ith shaped channel. UE This indicates the number of target user devices.

15. The electronic device according to claim 11, characterized in that, The second weighting coefficient satisfies: Where, α i σ represents the second weighting coefficient of all paired user equipment under i shaped channels, μ represents the average signal-to-noise ratio of all shaped channels before channel selection, and σ represents the average signal-to-noise ratio of all shaped channels before channel selection. 2 Rsrp represents the average noise power of all shaped channels before channel selection. i This represents the sum of the reference signal received power of all paired user equipment in the i-th shaped channel.

16. The electronic device according to claim 15, characterized in that, The operation also includes: The uplink signal power of the target shaping channel is determined based on the product of the second reference signal received power and the second weighting coefficient.

17. The electronic device according to claim 16, characterized in that, The uplink signal power of the target shaping channel is determined by the following calculation formula: in, α represents the uplink signal power of the i-th shaped channel out of Nr shaped channels. i This represents the second weighting coefficient of all paired user equipment in the i-th shaping channel. N represents the reference signal received power of the j-th paired user equipment in the i-th shaped channel. UE This indicates the number of paired user devices.

18. The electronic device according to any one of claims 13 or 16, characterized in that, After determining the uplink signal power of the target shaping channel, the method further includes: The shaping channels are sorted in descending order based on the uplink signal power to determine a preset number of shaping channels.

19. A shaping channel selection weight determination device, characterized in that, include: The first determining unit is used to determine a first weighting coefficient or a second weighting coefficient corresponding to the target beamforming channel based on the reference signal received power parameters in the beamforming channel and the beamforming channel selection weighting determination model; the first weighting coefficient is the weighting coefficient of the target user equipment under the target beamforming channel, and the second weighting coefficient is the weighting coefficient of all paired user equipments under the target beamforming channel after multi-user pairing is completed. The reference signal received power parameter is either the first reference signal received power corresponding to the target user equipment, or the second reference signal received power corresponding to all paired user equipment, wherein the second reference signal received power is the sum of the reference signal received powers corresponding to all paired user equipment; the beamforming channel selection weight determination model is an optimization model that optimizes the weight coefficients by taking maximizing the channel capacity of the multiple-input multiple-output MIMO channel as the optimization objective and using the Kuhn-Tak condition and the average allocation constraint as constraints.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that enables a computer to perform the method according to any one of claims 1 to 9.

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