Base station power adjustment method, electronic device and storage medium

Abstract

Provided in the present application are a base station power adjustment method, an electronic device and a storage medium, which are applied to a co-frequency co-time full duplex (CCFD) communication network. The method comprises: on the basis of base station measurement data of a communication network, determining an initial CCFD interference parameter and an initial user perception parameter of each base station in the communication network; under the constraint of a CCFD dimension condition and a user perception dimension condition, optimizing the base station efficiency of the communication network on the basis of the initial CCFD interference parameter and the initial user perception parameter of each base station in the communication network, so as to obtain a target power configuration of each base station in the communication network; and determining a base station power adjustment strategy of a base station group on the basis of the target power configurations of the base stations, so as to adjust the power of some base stations in the communication network according to the base station power adjustment strategy.

Description

Base station power adjustment method, electronic device and storage medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to a Chinese patent application filed with the Patent Office of China on June 28, 2023, with application number 202310782108.X and invention name “A base station power adjustment method, electronic device and storage medium”. The entire contents of the Chinese patent application are incorporated herein by reference. Technical Field

[0003] The present application relates to the field of communication technology, and in particular to a base station power adjustment method, electronic equipment, and storage medium. Background Art

[0004] Based on co-frequency co-time full duplex (CCFD) technology, communication devices can use the same time and frequency to transmit and receive wireless signals, thereby improving the spectral efficiency of wireless communication links. As a key technology for improving spectral efficiency, CCFD also has some challenges that need to be overcome. For example, when transmitting and receiving simultaneously on the same frequency, the transmitter's transmitted signal can interfere with the local receiver. Therefore, eliminating this interference is key to ensuring CCFD communication quality.

[0005] In recent years, with the introduction of CCFD, communication networks have gradually adopted a networking approach that overlaps traditional macro and CCFD base stations. However, macro and CCFD base stations utilize different resource allocation methods. Currently, when optimizing base station performance in communication networks, using traditional power allocation strategies for macro base stations cannot guarantee communication quality for CCFD base stations.

[0006] Summary of the Invention

[0007] The purpose of this application is to provide a base station power adjustment method, electronic device and storage medium, which can optimize the base station performance of the communication network while ensuring CCFD communication quality and user perception quality, and determine the relatively optimal base station power configuration of the communication network.

[0008] In order to achieve the above-mentioned purpose, the embodiment of the present application is implemented as follows.

[0009] In a first aspect, a base station power adjustment method is provided, which is applied to a communication network with simultaneous full-duplex CCFD at the same frequency, comprising: determining the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network based on the base station measurement data of the communication network; optimizing the base station performance of the communication network based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network under the constraints of CCFD dimension conditions and user perception dimension conditions, and obtaining the target power configuration of each base station in the communication network; determining the base station power adjustment strategy of the communication network based on the target power configuration of each base station, so as to perform power adjustment on at least some base stations in the communication network according to the base station power adjustment strategy.

[0010] In a second aspect, an embodiment of the present application provides an electronic device, comprising: a processor; and a memory configured to store computer-executable instructions, wherein the computer-executable instructions, when executed, cause the processor to execute the method described in the first aspect.

[0011] According to a third aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium is used to store computer-executable instructions, and the computer-executable instructions implement the method described in the first aspect when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0013] FIG1 is a schematic diagram of a first flow chart of a base station power adjustment method provided in an embodiment of the present application.

[0014] FIG2 is a second flow chart of the base station power adjustment method provided in an embodiment of the present application.

[0015] FIG3 is a third flow chart of the base station power adjustment method provided in an embodiment of the present application.

[0016] FIG4 is a fourth flow chart of the base station power adjustment method provided in an embodiment of the present application.

[0017] FIG5 is a fifth flow chart of the base station power adjustment method provided in an embodiment of the present application.

[0018] FIG6 is a schematic structural diagram of a base station power adjustment device provided in an embodiment of the present application.

[0019] FIG7 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] As mentioned earlier, with the introduction of CCFD, existing communication networks have gradually adopted a networking approach that overlaps traditional macro base stations with CCFD base stations. Unlike macro base stations, CCFD base stations can transmit and receive wireless signals using the same time and frequency, resulting in significantly different resource allocation methods. This leads to highly complex inter-channel interference in the communication network. When optimizing base station performance in a communication network, using traditional power allocation strategies similar to those for macro base stations will not guarantee communication quality for CCFD base stations.

[0021] In view of this, the present application aims to propose a base station power adjustment scheme that can optimize the base station performance of the communication network while ensuring CCFD communication quality and user perception quality, thereby adjusting it according to the relatively optimal base station power configuration.

[0022] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this specification.

[0023] For co-frequency, full-duplex CCFD communication networks, such as traditional macro base stations and CCFD stations, or CCFD stations collaborating in a network, an embodiment of the present application provides a base station power adjustment method. Figure 1 is a schematic diagram of the base station power adjustment process, which specifically includes the following steps.

[0024] S102: Determine initial CCFD interference parameters and initial user perception parameters of each base station in the communication network based on base station measurement data of the communication network.

[0025] In this embodiment, the base station measurement data reflects the operating status of the base stations in the communication network, and can be collected through means such as channel correlation measurement, scheduling policy reporting, and user measurement reporting.

[0026] The CCFD interference parameters reflect the level of CCFD interference and may include: cross-link interference (CLI) and self-interference (SI) of the base station; the initial CCFD interference parameters described in this embodiment refer to the CCFD interference parameters corresponding to the communication network under the current base station power configuration.

[0027] User perception parameters reflect the user's perception level and may include the user's signal-to-interference plus noise ratio (SINR), the frequency scheduling order used by the base station modulation and coding scheme (MCS), and the user-level rate. Similarly, the initial user perception parameters described in this embodiment refer to the user perception parameters corresponding to the communication network under the current base station power configuration.

[0028] S104: Under the constraints of CCFD dimension conditions and user perception dimension conditions, the base station performance of the communication network is optimized based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network to obtain the target power configuration of each base station in the communication network.

[0029] In this embodiment, CCFD dimension conditions refer to restrictions on CCFD interference parameters while ensuring normal service operation of the communication network; for example, cross-link interference and self-interference of a base station must be below a certain level. Similarly, user perception dimension conditions refer to restrictions on user perception parameters while ensuring normal service operation of the communication network; for example, the user-level rate must reach at least a certain level.

[0030] In one example, a quantitative relationship between CCFD interference parameters, user perception parameters, and base station performance of the communication network can be constructed. With CCFD dimension requirements and user perception dimension requirements as constraints, the base station performance of the communication network is iteratively optimized based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network to determine the target power configuration of each base station when the communication network achieves the relatively optimal base station performance.

[0031] The iterative principle is to determine the current initial base station performance based on the current initial base station power configuration of the communication network, combined with the initial CCFD interference parameters and initial user perception parameters. Then, under the constraints of the CCFD interference parameters and user perception parameters, try to adjust some base station configurations in the communication network. If the performance of the adjusted base station is improved, the base station configuration is used to enter the next round of iteration, and further attempts are made to adjust the base station configuration. Through continuous iteration in this way, the performance of the communication network base stations can be optimized.

[0032] As an example, this embodiment may introduce adjustments to the channel relationship between the base station and the user (ie, the base station configuration) during the iteration process to improve the base station performance of the communication network.

[0033] That is, under the constraints of CCFD dimensional conditions and user perception dimensional conditions, the channel relationship between each base station and the user is first optimized for multiple rounds of iterations based on the initial CCFD interference parameters and initial user perception parameters of the base station (the channel relationship between the base station and the user is coupled with the CCFD interference parameters and user perception parameters of the base station) to determine the target user association corresponding to each base station when the relatively optimal channel relationship is achieved.

[0034] Next, given the target user association of each base station, the power configuration of each base station is optimized with the gradient of maximizing the base station efficiency of the communication network as the gradient, and the target power configuration of each base station after optimization is determined. For example, a search optimization algorithm is used, with the power configuration of each base station as the search position of the search optimization algorithm, and the number of users in service at each base station as the search space of the search optimization algorithm. A pre-set fitness function is used to determine the gradient direction that maximizes the base station efficiency of the communication network (in the fitness function, the search position is coupled with the base station efficiency of the communication network). Multiple rounds of iterative search optimization are then performed on the power configuration of each base station according to this gradient direction to determine the target power configuration of each base station.

[0035] S106: Determine a base station power adjustment strategy for the communication network based on the target power configuration of each base station, so as to perform power adjustment on at least some base stations in the communication network according to the base station power adjustment strategy.

[0036] Typically, the total base station power quota of a communication network is fixed. To prevent the adjusted total base station power from exceeding the quota, this embodiment may employ power migration between base stations to perform scalability adjustment.

[0037] That is, a group of base stations in an energy efficiency cooperative relationship in the communication network is predetermined, wherein the energy efficiency cooperative relationship refers to a relationship between base stations that can perform power scheduling with each other, which is a priori knowledge in this embodiment.

[0038] Then, based on the initial power configuration and target power configuration of each base station in the base station group, the base station group is divided into a disturbing base station set and a disturbed base station set. The disturbing base stations are the base stations whose power is to be switched out, and the disturbed base stations are the base stations whose power is to be switched in. If a base station's target power configuration is greater than its initial power configuration, it indicates that its current power configuration needs to be increased, and it is therefore classified as a disturbed base station. Conversely, if a base station's target power configuration is less than its initial power configuration, it indicates that its current power configuration needs to be reduced, and it is therefore classified as a disturbing base station.

[0039] Next, based on the correlation coefficient and transferable power between the interfering base station and the interfered base station, the preference between the interfering base station in the interfering base station set and the interfered base station in the interfered base station set is determined. The correlation coefficient between the base stations is pre-set, for example, the correlation coefficient between base stations with the same service type and channel type is set to a higher level, and the correlation coefficient between base stations with different service types and channel types is set to a lower level. The transferable power is the smallest value selected from the transferable power of the interfering base station (the difference between the initial power configuration and the target power configuration) and the transferable power of the interfered base station (the difference between the target power configuration and the initial power configuration). For example, if the transferable power of the interfering base station is 60 watts and the transferable power of the interfered base station is 50 watts, then the transferable power between the interfering base station and the interfered base station is 50 watts. In this embodiment, the higher the correlation coefficient and transferable power between the interfering base station and the interfered base station, the higher the corresponding preference; conversely, the lower the correlation coefficient and transferable power, the lower the corresponding preference.

[0040] Afterwards, a target interfering base station and a target disturbed base station whose preferences meet a preset standard (the preferences meet a certain threshold requirement) are selected from the interfering base station set and the disturbed base station set, and a power adjustment strategy is determined to transfer part of the power of the target interfering base station to the target disturbed base station. For example, if the target interfering base station can transfer out 100 watts of power and the target disturbed base station can transfer in 50 watts of power, then a power adjustment strategy can be determined to transfer 50 watts of the target interfering base station to the target disturbed base station. For another example, if the target interfering base station can transfer out 60 watts of power and the target disturbed base station can transfer in 100 watts of power, then a power adjustment strategy can be determined to transfer 60 watts of the target interfering base station to the target disturbed base station.

[0041] Based on the above content, it can be seen that: when optimizing the base station performance of the communication network, the method of this embodiment first performs base station measurements on the communication network to obtain the current initial CCFD interference parameters and initial user perception parameters of each base station. Afterwards, based on the initial CCFD interference parameters and initial user perception parameters of each base station, the base station performance of the communication network is optimized under the constraints of CCFD dimensional conditions and user perception dimensional conditions, so as to obtain the optimal or near-optimal solution for the power configuration of each base station while taking into account better user experience and lower CCFD interference, thereby guiding the base station power adjustment of the communication network. The method of this embodiment is applicable to network environments with very complex interference channels such as traditional macro stations and CCFD base stations co-networking and CCFD base stations collaborative networking, and can effectively improve the energy utilization rate of the communication network.

[0042] The base station power adjustment method of this embodiment is described in detail below.

[0043] Compared to traditional macro base stations, CCFD base stations use flexible frame structure technology, which can dynamically adjust power configuration according to changes in service load. To this end, this embodiment uses the granularity of each service in the communication network to optimize the base station efficiency of the communication network.

[0044] It should be noted that different business scenarios correspond to different user perception dimension conditions.

[0045] As an example, communication network services can be divided into three types based on their characteristics: Service Scenario A (low latency), Service Scenario B (high downlink traffic), and Service Scenario C (high uplink traffic). Service Scenario A prioritizes latency, thus requiring a higher user signal-to-noise ratio (SNR), but only requires the user-level rate to meet a minimum threshold. Service Scenarios B and C, on the other hand, require optimal channel quality while also ensuring smooth service handover, thus placing higher demands on the user SNR and frequency scheduling order.

[0046] This embodiment takes the target business scenario as an example (the target business scenario can be any of business scenarios A, B, and C), and optimizes the base station performance of the communication network according to the restrictions on user perception parameters and general CCFD interference parameters of the target business.

[0047] In one example, it is assumed that there are m∈{1,2,3,…,M+1} base stations in the communication network, where user j∈{1,2,3,…,N}, M+1 <N,x jm Represents the access relationship between user j and base station m.

[0048] Based on the asymmetric uplink and downlink characteristics of CCFD base stations, the following definitions are made.

[0049] The user signal-to-noise ratio (SINR) is defined as shown in the following formula 1.

[0050] Among them, γ jm is the signal-to-noise ratio between user j and base station m, P jm is the transmission power of base station m to user j, h jm is the channel gain between user j and base station m, is the transmission power of other base stations to user j, is the interference channel gain of other base stations, δ 2 is additive white Gaussian noise. is the cross-layer co-frequency cross-link interference of other base stations, denoted as Cli jm ∑ j‘∈m,j‘≠j |h j‘m | 2 x j‘m P j‘m is the internal self-interference of base station m, expressed as Sicjm .

[0051] The actual user-level rate of user j associated with base station m is defined as formula 2. jm =Wlog2(1+γ jm ) (Formula 2)

[0052] The base station energy efficiency of the communication network is defined as Formula 3.

[0053] in, The overall base station energy efficiency of the communication network, is the transmission power of base station m, is the base station’s transmit power amplification factor, The circuit energy efficiency of the base station.

[0054] Taking into account the constraints of CCFD dimensional conditions and user perception dimensional conditions, the objective problem P1 is defined as maximizing the base station energy efficiency of the communication network. Then P1 is shown in the following formula 4.

[0055] Where X = [x jm ],P=[P jm ], C1 and C2 are constraints associated with user base stations, C3 is the constraint on user perceived rate, C4 is the CLI interference constraint, C5 is the SI interference constraint, and C6 is the constraint on base station transmit power.

[0056] Due to the nonlinear characteristics of P1 and the randomness of network eigenvalues, the solution process is very complex. Therefore, this embodiment splits P1 into three sub-problem models, namely the user association model, the network power consumption retrieval model, and the energy efficiency matching collaboration model.

[0057] The user association model is used to reshape the connection relationships between users at each base station in the communication network to determine the target user association corresponding to each base station when achieving a relatively optimal channel relationship. The network power consumption search is used to perform multiple rounds of iterative search and optimization of the power configuration of each base station based on the target user association provided by the user association model to determine the relatively optimal target power configuration for each base station. The energy efficiency collaboration model is used to determine the power adjustment strategy for transferring part of the power of the interfering base station to the interfered base station based on the relatively optimal target power configuration of each base station.

[0058] Based on the model configuration of the above three sub-problems, the overall process of this embodiment is shown in Figure 2, which includes the following steps.

[0059] S21, under the current initial power configuration of each base station in the communication network, the status of each base station in the communication network running the target service is measured through existing measurement methods such as channel correlation measurement, scheduling strategy reporting, and user measurement reporting, and the base station measurement data corresponding to the target service of the communication network is obtained.

[0060] S22, setting the convergence condition of the base station energy efficiency of the communication network and the number of iterative optimization rounds according to the network scale of the communication network and the performance requirements of the target service.

[0061] It should be understood that the iterative optimization process ends when the energy efficiency of the base stations of the communication network reaches a convergence condition or when the number of iterative rounds is completed.

[0062] S23 , determining the target user association corresponding to each base station when a relatively optimal channel relationship is achieved based on the user association model.

[0063] In one example, the execution flow of the user association model is shown in FIG3 .

[0064] First, the current power configuration of each base station in the communication network and the base station groups in the communication network that belong to the energy efficiency cooperation relationship are given.

[0065] Next, enter the iterative process.

[0066] Under the constraints of CCFD and user perception, the user association degree corresponding to each base station in the base station group under the current user connection relationship is calculated based on the power configuration, CCFD interference parameters, and user perception parameters of each base station in the base station group in the current iteration. In the first iteration, the power configuration of each base station adopts the initial power configuration described above, the CCFD interference parameters of each base station adopt the initial CCFD interference parameters described above, and the user perception parameters of each base station adopt the initial user perception parameters described above.

[0067] The CCFD interference parameters and user perception parameters are changed to reshape the user connection relationship of each base station in the base station group to update the user association degree of each base station in the base station group.

[0068] If the user association degree of each base station in the updated base station group is improved (not converged yet), the next round of iteration is entered; otherwise, the iteration process ends and the user association degree of each base station in the base station group determined by this round of iteration is output.

[0069] Among them, the calculation principle of the user association model is as follows.

[0070] The subproblem P2 that defines the user relevance model is shown in Formula 5. P2: maxEE(X) stC1,C2,C3,C4,C5 (Formula 5)

[0071] For continuous convex optimization problems, the Lagrange dual method is used to solve them. The Lagrange multiplier γ is introduced. j and θ m (i.e., correlation factor), converting the inequality constraint into an equality constraint. The converted formula is shown in Formula 6 below.

[0072] Defining the optimal user association EE jm Function, used to calculate the channel correlation between user j and each base station m, according to user Sinr jm ,Mcs jm and Cli jm ,Sic jm Calculate and solve the relatively optimal channel relationship (Mcs jm With Sinr jm Equivalent), the optimization problem after reshaping can be expressed as shown in the following formula 7.

[0073] During the iteration process, the user association function EE of each base station is first calculated according to Formula 7 jm , select the maximum user association. Secondly, according to the minimum constraint of user perception and base station transmission power constraint and gradient descent requirements, determine the Lagrange multiplier γ before and after iteration j and θ m Update the relationship as shown in Formulas 7-1 and 7-2.

[0074] Among them, δ(t) is the iteration step, which is set according to the computing power, and t is the number of iterations. After the update is completed, if the user association of the previous and next iterations is the same, that is, x jm (t+1)=x jm (t) End the iteration, otherwise calculate the iterative calculation.

[0075] It should be noted that the channel relationship reshaped by formulas 6 and 7 can be adapted according to the target business scenario. Business scenario A prioritizes latency, so τ jm Only the minimum threshold is required, but for Sinr jm The requirements are high, so γ j The initial value is small, θ m The initial value is large; in business scenarios B and C, in order to ensure the best channel quality and take into account smooth business switching, Sinr jm 、Mcs jm The requirements are high, so γ j ,θ m The initial values ​​are all large.

[0076] It can be seen that the above iterative process reorganizes the uplink and downlink channel relationship according to the channel relationship between the user and other base stations, breaking the constraint of transmitting the unique uplink and downlink relationship between the user and the base station, and is more suitable for CCFD. The final iteration can solve the user association degree m under the relatively optimal channel relationship of the base station * .

[0077] S24, performing multiple rounds of iterative search optimization on the power configuration of each base station based on the network power consumption retrieval model to determine the relatively optimal target power configuration of each base station.

[0078] The search optimization in this embodiment specifically adopts the particle swarm optimization algorithm.

[0079] The main parameters of the particle swarm optimization algorithm include: group size m, inertia weight w, acceleration constants c1 and c2, maximum speed Vmax, and maximum number of iterations Gmax.

[0080] The particle swarm optimization algorithm specifies that each particle has a position and velocity, which represent the search unit's position and direction of movement in multidimensional space, respectively. Vmax determines the resolution (or accuracy) of the region between the current position and the best position. The inertia weight w maintains the particle's inertia, allowing it to expand the search space and explore new areas. The acceleration constants c1 and c2 represent the weights of the statistical acceleration term that pushes each particle toward the pbest and gbest positions.

[0081] The standard calculation process of the particle swarm optimization algorithm is as follows.

[0082] Initialize a swarm of particles (swarm size is m) with random positions and velocities.

[0083] Evaluate the fitness of each particle.

[0084] For each particle, compare its fitness value with the best position pbest it has ever experienced. If it is better, it will be used as the current best position pbest.

[0085] For each particle, its fitness value is compared with the best position gbest experienced globally. If it is better, the index number of gbest is reset.

[0086] If the fitness value of the particle reaches a certain level or the maximum number of iterations is reached, the iteration ends; otherwise, the speed and position of the particle are updated and the next round of iteration is entered.

[0087] Based on the principle of the above-mentioned particle swarm optimization algorithm, this embodiment uses the power configuration of each base station as the search position (particle position), the number of users in service of each base station as the search space, and the normalized channel quality and interference constraints as weights. Through a pre-set fitness function (in the fitness function, the search position is coupled with the base station efficiency of the communication network), the power configuration of each base station is searched and optimized for multiple rounds in the gradient direction of maximizing the base station efficiency of the communication network. The optimal solution set of power allocation for each base station, i.e., the target power configuration, can be calculated.

[0088] Correspondingly, the execution process of the network power consumption retrieval model is shown in FIG4 , which includes the following steps.

[0089] First, a group of base stations in an energy efficiency cooperative relationship in a given communication network and the target user association degree of each base station in the base station group are given.

[0090] Afterwards, the search factor is initialized, that is, the power configuration of each base station is used as the search position of the search optimization algorithm, and the number of in-service users of each base station is used as the search space of the search optimization algorithm; and the global and local optimal solution sets and fitness functions are defined based on the target user association of each base station in the base station group.

[0091] Next, enter the iterative process.

[0092] Determine whether the maximum number of iterations has been reached in this round of iterations; if so, output the global optimal solution determined by this round of iterations and end the iteration process; if not, continue execution.

[0093] The weights (channel quality and interference constraints) are updated to calculate the globally optimal particle position. To avoid falling into the local optimal solution set and the problem of low precision in high-dimensional nonlinearity, the particle position is calculated using a global search method in the first half of the iterations and a local search method in the second half of the iterations.

[0094] Substitute the search position of this iteration into the fitness function to calculate the current fitness of this iteration.

[0095] Update the particle speed and position, calculate the fitness of each particle, and determine the global and local optimal solutions for this round of iteration.

[0096] Among them, the calculation principle of the network power consumption retrieval model is as follows.

[0097] The subproblem P3 of the network power consumption retrieval model is defined as shown in Formula 8. P3:maxEE(P) stC4,C5,C6 (Formula 8)

[0098] Based on the particle swarm optimization algorithm, the particle x idDefined as a set of feasible solutions P for the variables P in the optimization problem * , define the fitness function as the base station efficiency EE(P) of the communication network, locate the number of users in the spatial dimension, and define the global optimal position gBest id and the local optimal position pBest id The particle position and velocity are continuously updated according to the global optimal solution and the local optimal solution, as shown in the following formula 9 and formula 10. id (t+1)= wv id (t)+c1rand(pBest id (t)-x id (t))+c2rand(gBest id (t)-x id (t)) (Formula 9) x id (t+1)=v id (t+1)+x id (t) (Formula 10)

[0099] Among them, c1 and c2 are particle swarm learning factors, determined based on the network scale and optimization depth. In normal networking scenarios, they can be set to larger values ​​to enhance global search capabilities, while in ultra-dense networking scenarios, they can be set to smaller values ​​to improve local traversal capabilities and accurately calculate local optimal solutions. Furthermore, the weight w is adjusted based on the search speed, and the search particle speed can be set according to service switching requirements. Service scenario A prioritizes latency, so the weight w can be set to a larger value. Service scenarios B and C prioritize user perception while also taking into account smooth service switching, so the weight w can be set to a smaller value. Furthermore, to prevent the iterative solution process from falling into the local optimal solution set and the problem of low precision in high-dimensional nonlinearity, the optimization solution process is divided into a first-half global search and a second-half local search. Dynamic weighting strategies are used in both stages to enhance search capabilities. In service scenarios B and C, to ensure optimal channel quality while taking into account smooth service switching, the number of iterations in the first half can be slightly less than the number of iterations in the second half, focusing the search on local search.

[0100] During the iteration process, the global optimal position gBest is initialized according to the given initial base station power id and the local optimal position pBest id After that, c1, c2, and w are set based on the network size and optimization depth. The weight w can be set based on the search speed and number of iterations, as shown in Formula 10-1.

[0101] Among them, t is the current iteration number, T max is the maximum number of iterations, and J is the number of iterations of the front and back segments.

[0102] It should be understood that pBest can be calculated according to formula 10, 10-1 id , find the maximum EE(P) as gBest id Afterwards, according to pBest id ,gBest id Update the particle position and velocity and enter the next round of iterative calculation until the iteration ends.

[0103] The network power consumption retrieval model of this embodiment can quickly and efficiently traverse the user channel relationship base station m * There are adjacent base stations that can release energy efficiency resources, and the traversal process takes into account Cli jm ,Sic jm Interference constraints therefore do not affect user perception and can significantly improve both Sinr and Mcs.

[0104] S25: Based on the energy efficiency matching cooperation model, determine a power adjustment strategy for transferring part of the power of the interfering base station to the interfered base station.

[0105] In one example, the execution process of the user association model is shown in FIG5 , and includes the following steps.

[0106] Firstly, given a group of base stations in an energy efficiency cooperative relationship in a communication network, the base station group is divided into a interfered base station set and an interfering base station set.

[0107] Next, according to a preset preference function, the preferences between the interfering base stations in the interfering base station set and the disturbed base stations in the disturbed base station set are determined, and the base stations are sorted from high to low according to the preference.

[0108] Then, according to the preference ranking, a target interfering base station and a target interfered base station are extracted from the interfering base station set and the interfered base station set, and a power adjustment strategy is determined to transfer part of the power of the target interfering base station to the target interfered base station.

[0109] Then, determine whether the disturbing base station set and the disturbed base station set are empty; if yes, end; if not, continue to extract new target disturbing base stations and target disturbed base stations from the disturbing base station set and the disturbed base station set to determine the power adjustment strategy.

[0110] Among them, the calculation principle of the energy efficiency matching collaboration model is as follows.

[0111] Given the base station power configuration, user-associated base station m * , Base station power consumption search results P * Under this relationship, the base station energy efficiency adjustment problem of the communication network is defined as P4, as shown in the following formula 11. P4:maxEE(G) stC3,C4,C5,C6 (Formula 11)

[0112] The base station group in the energy efficiency cooperation relationship is divided into the interfered base station group and the interfering base station set Establish A based on channel relevance and business model (user perception dimension condition of target business) - and A + The preference function between is shown in the following formula 12. P(A + ,A - )=αP mm |m - ∈A - (Formula 12)

[0113] Among them, α represents the correlation coefficient between the disturbed and disturbing base stations, P mm Indicates the maximum power that can be transmitted between base stations.

[0114] The base stations in the disturbed base station set and the disturbing base station set are sorted according to the preference function. The disturbing base station completes energy efficiency transmission to the disturbed base station according to the preference. The energy efficiency transmission process requires the disturbing base station to reduce its output power and the disturbed base station to increase its output power. After the transmission is completed, it is removed from the current set until both sets are empty and the energy efficiency matching allocation is completed, thereby obtaining the power allocation adjustment strategy for each base station.

[0115] S26, determine whether the base station energy efficiency of the communication network meets the convergence conditions and the number of iterative optimization rounds; if yes, execute S27; if not, return to step 23.

[0116] S27: Output the final power adjustment strategy.

[0117] In summary, this embodiment defines three models: user relevance, network power consumption search, and energy efficiency collaboration. This model is formulated based on the optimal solution set for user perception and system energy efficiency, expressed as a multi-constrained non-convex optimization problem. Channel correlation, scheduling strategy, and user measurements are incorporated into the model's adaptive training, and the optimization solution set is iteratively solved to determine the adjustment range for network-related parameters. Furthermore, the multi-constrained non-convex optimization problem is decomposed into three corresponding non-convex optimization subproblems, reducing the iterative complexity of the problem and improving its feasibility.

[0118] Corresponding to the base station power adjustment method shown in Figure 1, another embodiment of the present application further provides a base station power adjustment device for a communication network applied to CCFD. Figure 6 is a schematic structural diagram of a base station power adjustment device 600, which includes the following modules.

[0119] The testing module 610 is configured to determine an initial CCFD interference parameter and an initial user perception parameter of each base station in the communication network based on base station measurement data of the communication network.

[0120] The optimization module 620 is used to optimize the base station performance of the communication network based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network under the constraints of CCFD dimension conditions and user perception dimension conditions, and obtain the target power configuration of each base station in the communication network.

[0121] The adjustment module 630 is configured to determine a base station power adjustment strategy of the communication network based on the target power configuration of each base station, so as to perform power adjustment on at least some base stations in the communication network according to the base station power adjustment strategy.

[0122] When optimizing the base station performance of a communication network, the device of this embodiment first performs base station measurements on the communication network to obtain the current initial CCFD interference parameters and initial user perception parameters of each base station. Afterwards, based on the initial CCFD interference parameters and initial user perception parameters of each base station, the base station performance of the communication network is optimized under the constraints of CCFD dimensional conditions and user perception dimensional conditions, so as to obtain the optimal or near-optimal solution for the power configuration of each base station while taking into account a better user experience and lower CCFD interference, thereby guiding the adjustment of the base station power of the communication network. The device of this embodiment is suitable for network environments with very complex interference channels, such as traditional macro stations and CCFD base stations co-networking, and CCFD base stations collaborative networking, and can effectively improve the energy utilization rate of the communication network.

[0123] In one embodiment, the optimization module 620 optimizes the base station efficiency of the communication network based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network under the constraints of CCFD dimension conditions and user perception dimension conditions, and obtains the target power configuration of each base station in the communication network, including: optimizing the channel relationship between each base station and the user based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network under the constraints of CCFD dimension conditions and user perception dimension conditions, and determining the target user association of each base station; given the target user association of each base station, optimizing the power configuration of each base station with maximizing the base station efficiency of the communication network as the gradient, and determining the target power configuration of each base station.

[0124] Among them, the optimization module 620 optimizes the power configuration of each base station with the maximization of the base station efficiency of the communication network as the gradient given the target user association of each base station, and determines the target power configuration of each base station, including: given the target user association of each base station, using the power configuration of each base station as the search position of the search optimization algorithm, using the number of in-service users of each base station as the search space of the search optimization algorithm, through a pre-set fitness function, according to the gradient direction of maximizing the base station efficiency of the communication network, performing multiple rounds of iterative search optimization on the power configuration of each base station to determine the target power configuration of each base station.

[0125] In one embodiment, the search optimization of the first iterative portion of the search optimization algorithm adopts a global search method, and the search optimization of the second iterative portion adopts a local search method.

[0126] Among them, the adjustment module 630 determines the base station power adjustment strategy of the communication network based on the target power configuration of each base station, so as to perform power adjustment on at least part of the base stations in the communication network according to the base station power adjustment strategy, including: given a group of base stations belonging to an energy efficiency collaboration relationship in the communication network, determining the base station power adjustment strategy of the base station group based on the target power configuration of each base station in the base station group; wherein the energy efficiency collaboration relationship refers to a relationship between base stations that can perform power scheduling with each other; and performing power adjustment on each base station in the base station group according to the base station power adjustment strategy.

[0127] In one embodiment, the adjustment module 630, given a group of base stations in an energy efficiency cooperative relationship in the communication network, determines a base station power adjustment strategy for the base station group based on the target power configuration of each base station in the base station group, including: dividing the base station group into a disturbing base station set and a disturbed base station set based on the initial power configuration and target power configuration of each base station in the base station group; determining a preference between disturbing base stations in the disturbing base station set and disturbed base stations in the disturbed base station set; selecting a target disturbing base station and a target disturbed base station whose preference meets a preset standard from the disturbing base station set and the disturbed base station set, and determining a power adjustment strategy to transfer part of the power of the target disturbing base station to the target disturbed base station.

[0128] In one embodiment, the user perception parameter includes at least one of a user signal-to-noise ratio, a frequency scheduling order, and a user-level rate of the base station; and the CCFD interference parameter includes at least one of a cross-link interference and a self-interference of the base station.

[0129] In one embodiment, before determining the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network based on the base station measurement data of the communication network, the test module 610 also measures the conditions of each base station in the communication network operating the target business scenario to obtain the base station measurement data of the communication network; wherein the user perception dimension requirements include restrictions on the user perception parameters of the target business scenario.

[0130] It should be understood that the base station power adjustment device of this embodiment can serve as the execution subject of the method shown in FIG1 , and thus can implement the steps and functions in the method shown in FIG1 .

[0131] FIG7 is a schematic diagram of the structure of an electronic device according to an embodiment of the present specification. Referring to FIG7 , at the hardware level, the electronic device includes a processor, and may also include an internal bus, a network interface, and a memory. The memory may include internal memory, such as high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device. Of course, the electronic device may also include hardware required for other services.

[0132] The processor, network interface, and memory can be interconnected via an internal bus, such as an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. These buses can be categorized as address buses, data buses, and control buses. For ease of illustration, FIG7 shows only one bidirectional arrow, but this does not imply that there is only one bus or only one type of bus.

[0133] A memory is used to store programs. The programs may include program code, which includes computer operating instructions. The memory may include internal memory and non-volatile memory, and provides instructions and data to the processor.

[0134] In one embodiment, the processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs it, forming the base station power adjustment device shown in Figure 6 at the logical level. Correspondingly, the processor executes the program stored in the memory and is specifically configured to perform the following operations.

[0135] An initial CCFD interference parameter and an initial user perception parameter of each base station in the communication network are determined based on the base station measurement data of the communication network.

[0136] Under the constraints of CCFD dimensional conditions and user perception dimensional conditions, the base station performance of the communication network is optimized based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network to obtain the target power configuration of each base station in the communication network.

[0137] A base station power adjustment strategy for the base station group is determined based on the target power configuration of each base station, so as to adjust the power of some base stations in the communication network according to the base station power adjustment strategy.

[0138] The base station power adjustment method disclosed in the embodiments shown in this specification can be applied to a processor and implemented by the processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor or software instructions. The above processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of this application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of this application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0139] Of course, in addition to software implementation, the electronic device in this specification does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc. That is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0140] In addition, embodiments of the present application further provide a computer-readable storage medium storing one or more programs, each of which includes instructions. When executed by a portable electronic device including multiple application programs, the instructions enable the portable electronic device to perform the steps of the method shown in FIG. 1 , including the following steps.

[0141] An initial CCFD interference parameter and an initial user perception parameter of each base station in the communication network are determined based on the base station measurement data of the communication network.

[0142] Under the constraints of CCFD dimensional conditions and user perception dimensional conditions, the base station performance of the communication network is optimized based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network to obtain the target power configuration of each base station in the communication network.

[0143] A base station power adjustment strategy for the base station group is determined based on the target power configuration of each base station, so as to adjust the power of some base stations in the communication network according to the base station power adjustment strategy.

[0144] When optimizing the base station performance of a communication network, the electronic device of this embodiment first performs base station measurements on the communication network to obtain the current initial CCFD interference parameters and initial user perception parameters of each base station. Afterwards, based on the initial CCFD interference parameters and initial user perception parameters of each base station, the base station performance of the communication network is optimized under the constraints of the CCFD dimensional conditions and the user perception dimensional conditions, so as to obtain the optimal or near-optimal solution for the power configuration of each base station while taking into account a better user experience and lower CCFD interference, thereby guiding the adjustment of the base station power of the communication network. The electronic device of this embodiment is suitable for network environments with very complex interference channels, such as traditional macro stations and CCFD base stations co-networking, and CCFD base stations collaborative networking, and can effectively improve the energy utilization rate of the communication network.

[0145] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Thus, this specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0146] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0147] The above are merely examples of the present invention and are not intended to limit this specification. For those skilled in the art, various modifications and variations of this specification are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of this specification shall be included within the scope of the claims of this specification. In addition, all other embodiments obtained by those of ordinary skill in the art without creative effort shall fall within the scope of protection of this document.

Claims

1. A base station power adjustment method, applied to a communication network of simultaneous full-duplex CCFD with the same frequency, comprising: Determining initial CCFD interference parameters and initial user perception parameters of each base station in the communication network based on base station measurement data of the communication network; Under the constraints of CCFD dimension conditions and user perception dimension conditions, the base station performance of the communication network is optimized based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network to obtain the target power configuration of each base station in the communication network; A base station power adjustment strategy of the communication network is determined based on the target power configuration of each base station, so as to perform power adjustment on at least part of the base stations in the communication network according to the base station power adjustment strategy.

2. The method according to claim 1, wherein: The method optimizes the base station performance of the communication network based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network under the constraints of the CCFD dimensional condition and the user perception dimensional condition to obtain the target power configuration of each base station in the communication network, including: Under the constraints of CCFD dimension conditions and user perception dimension conditions, the channel relationship between each base station and the user is optimized based on the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network to determine the target user association degree of each base station; Given the target user association degree of each base station, the power configuration of each base station is optimized with maximizing the base station efficiency of the communication network as the gradient, and the target power configuration of each base station is determined.

3. The method according to claim 2, wherein: The step of optimizing the power configuration of each base station based on the target user association degree of each base station and maximizing the base station efficiency of the communication network as a gradient to determine the target power configuration of each base station includes: In the case of assigning the target user association degree to each base station, the power configuration of each base station is used as the search position of the search optimization algorithm, and the number of in-service users of each base station is used as the search The search space of the optimization algorithm performs multiple rounds of iterative search optimization on the power configuration of each base station through a pre-set fitness function in accordance with the gradient direction of maximizing the base station efficiency of the communication network to determine the target power configuration of each base station.

4. The method according to claim 3, wherein: The search optimization of the first part of the iteration of the search optimization algorithm adopts a global search method, and the search optimization of the second part of the iteration adopts a local search method.

5. The method according to claim 1, wherein: The determining the base station power adjustment strategy of the communication network based on the target power configuration of each base station, so as to perform power adjustment on at least some base stations in the communication network according to the base station power adjustment strategy, comprises: Given a group of base stations in an energy efficiency cooperative relationship in the communication network, determining a base station power adjustment strategy for the base station group based on a target power configuration of each base station in the base station group; wherein the energy efficiency cooperative relationship refers to a relationship between base stations that can perform power scheduling with each other; The power of each base station in the base station group is adjusted according to the base station power adjustment strategy.

6. The method according to claim 5, wherein: The method of determining the base station power adjustment strategy of the base station group based on the target power configuration of each base station in the base station group in a given communication network that belongs to an energy efficiency cooperation relationship includes: Based on the initial power configuration and the target power configuration of each base station in the base station group, the base station group is divided into an interfering base station set and a disturbed base station set; Determine a preference between a disturbing base station in the disturbing base station set and a disturbed base station in the disturbed base station set; A target disturbing base station and a target disturbed base station whose preferences reach a preset standard are selected from the disturbing base station set and the disturbed base station set, and a power adjustment strategy for transferring part of the power of the target disturbing base station to the target disturbed base station is determined.

7. The method according to any one of claims 1 to 6, wherein: The user perception parameter includes at least one of a user signal-to-noise ratio, a frequency scheduling order, and a user-level rate of the base station; The CCFD interference parameter includes at least one of cross-link interference and self-interference of the base station.

8. The method according to any one of claims 1 to 6, wherein: Before determining the initial CCFD interference parameters and initial user perception parameters of each base station in the communication network based on the base station measurement data of the communication network, the method further includes: The conditions of each base station in the communication network running the target business scenario are measured to obtain base station measurement data of the communication network; wherein the user perception dimension requirement includes restrictions on the user perception parameters of the target business scenario.

9. An electronic device, comprising: processor; And, a memory configured to store computer executable instructions, which, when executed, cause the processor to perform the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, wherein the computer-executable instructions implement the method according to any one of claims 1 to 8 when executed by a processor.

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