5G base station intelligent turn-off method based on VIP identification

Abstract

The invention discloses a 5G base station intelligent turn-off method based on VIP identification, which solves the problem of low user satisfaction caused by the fact that the overall performance of a cell is not considered in the prior art, and comprises the following steps: screening out base stations without VIP users based on the VIP attributes of the users in the base stations, and putting the base stations into a first turn-off candidate set; according to the flow attribute and the developed time of each service and the signal-to-noise ratio of the cell where the service is located, service quality screening is carried out, and the low-value service cells are included into a second turn-off candidate set; positioning light-load base stations according to the real-time load of each base station, and incorporating the light-load base stations into a third turn-off candidate set; and carrying out load transfer and turn-off on the base stations in the turn-off candidate set. According to the invention, the overall performance of the cell is considered, the optimization of the energy consumption of the 5G network system is realized on the premise that the service is online, and the user satisfaction is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and specifically provides a 5G base station intelligent shutdown method based on VIP identification. Background Art

[0002] The architecture of 5G base station equipment mainly adopts the AAU+BBU method. With distributed base stations becoming the mainstream base station construction method, the energy consumption ratio of the main base station equipment has gradually increased. Among them, the energy consumption of 5G equipment is higher than that of previous 3 / 4G equipment. Therefore, how to optimize the use of 5G networks, especially reducing energy consumption, is extremely important.

[0003] Existing 5G base station intelligent shutdown methods, for example, a "5G base station intelligent shutdown method, device, equipment and storage medium" disclosed in a Chinese patent document, with the publication number: CN113301599B, shut down base stations for pure Non-GBR services and services with poor quality such as delay and packet loss rate, so as to achieve the purpose of energy saving. However, this method only considers the single performance of the service and does not take into account the overall performance of the cell, including coverage performance and quality performance, etc. Therefore, after shutdown, situations such as poor signal-to-noise ratio (SNR) in the cell may occur, resulting in affecting user satisfaction. Summary of the Invention

[0004] In order to solve the problem of low user satisfaction caused by not considering the overall performance of the cell in the prior art, the present invention provides a 5G base station intelligent shutdown method based on VIP identification, which considers the overall performance of the cell and realizes the optimization of the energy consumption of the 5G network system on the premise that the service is online, ensuring user satisfaction.

[0005] The specific solution of the present invention is as follows.

[0006] A 5G base station intelligent shutdown method based on VIP identification includes: S1: Based on the VIP attributes of users in the base station, screen out the base stations without VIP users and include them in the first shutdown candidate set; S2: According to the traffic attributes and the elapsed time of each service, as well as the signal-to-noise ratio of the cell where it is located, perform service quality screening, and include low-value service cells in the second shutdown candidate set; S3: Locate lightly loaded base stations according to the real-time load of each base station and include them in the third shutdown candidate set; S4: Perform load transfer and shutdown on the base stations in the shutdown candidate set.

[0007] Starting from analyzing the important attributes of users, by evaluating the traffic attributes of the services carried out by users and combining with the signal-to-noise ratio, select low-value service cells as target cells to be eliminated, and select lightly loaded target base stations from them for load transfer and shutdown, that is, by means of differentiated 5G services, according to the needs of different users for different services, conditionally implement user migration between 5G base stations to achieve intelligent shutdown. Among them, the low-value service cells include low-traffic services under poor cell environment and high-traffic services that have timed out.

[0008] Further, the step S1 includes: performing a summation operation on the VIP attributes of all users running in each base station. If the operation result is greater than zero, mark the base station as a VIP base station, which cannot be shut down, and include all non-VIP base stations in the first shutdown candidate set, that is, according to the important attributes of users, mark each base station as a VIP cell, so as to preferentially ensure that the base stations where VIP users are located are not shut down.

[0009] Further, the step S2 includes: S21: Calculate the mathematical expectation of the elapsed time of all high-bandwidth services at the current moment of all base stations; S22: Set the signal-to-noise ratio threshold for low-bandwidth services and the signal-to-noise ratio threshold for high-bandwidth services, and mark the signal-to-noise ratio of each service in the base station; S23: Based on the signal-to-noise ratio marking of the services, mark the signal-to-noise ratio of each base station to generate a second shutdown candidate set.

[0010] By carefully analyzing each service, low-traffic services under poor cell environment can be screened out. By comprehensively analyzing the average running duration of high-traffic services, high-traffic services that have timed out can be obtained, and then a list of low-value services can be obtained.

[0011] Further, the step S21 includes: if the traffic attribute of the service is a high-bandwidth service, the count mark of the service is set to 1; if the traffic attribute of the service is a low-bandwidth service, the count mark of the service is set to 0; calculate the mathematical expectation based on the count mark. That is, calculate the mathematical expectation of the elapsed time of all high-bandwidth services at the current moment of the base station according to the traffic attribute and the elapsed time of each service in the base station, and then obtain high-traffic services that have timed out.

[0012] Further, the step S22 includes: If the service signal-to-noise ratio is less than the low-bandwidth service signal-to-noise ratio threshold, set the signal-to-noise ratio mark of the service to 1; If the service signal-to-noise ratio is greater than or equal to the high-bandwidth service signal-to-noise ratio threshold, set the signal-to-noise ratio mark of the service to 0; If the signal-to-noise ratio of a service is less than the high-bandwidth service signal-to-noise ratio threshold and the elapsed time of the service is greater than or equal to the mathematical expectation, then set the signal-to-noise ratio flag of the service to 1; otherwise, set it to 0.

[0013] By comprehensively analyzing the signal-to-noise ratio and elapsed time of services, low-traffic services in a poor cell environment and high-traffic services that have timed out are screened out, so as to perform load transfer and implement shutdown.

[0014] Further, the step S23 includes: if the signal-to-noise ratio flags of all services running in the base station are all 1, then set the signal-to-noise ratio flag of the base station to 1; otherwise, set it to 0; include all base stations with signal-to-noise ratio flags of 1 in the second shutdown candidate set, that is, screen out the base stations that only contain low-value services.

[0015] Further, the step S3 includes: setting a load threshold, and including all base stations with a load less than the load threshold in the third shutdown candidate set, so as to screen out target base stations with light loads for load transfer and implement shutdown.

[0016] Further, the step S4 includes: S41: Calculate the neighbor cell sets of the base stations in the shutdown candidate set to generate a transfer candidate set of the base stations; S42: Set a reference received power threshold, select the base stations in the transfer candidate set whose reference received power is not lower than the reference threshold and include them in the target set, and calculate the load margin of each base station in the target set. If the load of the base station to be shut down does not exceed the maximum load margin of the base stations in the target set, then perform load transfer and shutdown on the base station to be shut down.

[0017] Based on the received power quality of the target base stations, on the premise of ensuring user satisfaction, the 5G base stations of low-value services are shut down by means of neighbor cell migration, so as to optimize the energy consumption of the 5G network system.

[0018] Further, the step S41 specifically includes: Calculate the intersection of the three shutdown candidate sets, include the base stations that are simultaneously in the three shutdown candidate sets in the target shutdown base station set, and arrange them in ascending order according to the reference received power to generate an ascending set; Calculate the neighbor cell sets of each base station in the ascending set, and remove the cell lists in the neighbor cell sets that belong to the ascending set to generate a transfer candidate set of the base stations.

[0019] By taking the intersection of the first shutdown candidate set, the second shutdown candidate set, and the third shutdown candidate set and arranging them in ascending order, an ascending set of target shutdown base stations is generated, avoiding shutting down base stations according to the single performance of services, and achieving a comprehensive consideration of the overall performance of the cell, including coverage performance and quality performance, etc.

[0020] Further, step S4 further includes: S43: Set the upper limit of the number of base stations to be shut down. After executing step S42, if the number of shut-down base stations is less than the upper limit of the number of base stations to be shut down, continue to traverse the ascending set until the number of shut-down base stations reaches the upper limit of the number of base stations to be shut down or the ascending set is traversed.

[0021] Therefore, the present invention has the following beneficial effects: (1) Starting from analyzing the important attributes of users, by evaluating the traffic attributes of the services carried out by users and combining with the signal-to-noise ratio, low-value service cells are selected as target cells to be eliminated, and target base stations with light loads are selected from them for load transfer and implementation of shutdown. That is, by means of differentiated 5G services, according to the needs of different users for different services, the overall performance of the cell, including coverage performance and quality performance, etc., is comprehensively considered, and conditional user migration between 5G base stations is implemented to achieve intelligent shutdown; (2) It can shut down 5G base stations with low-value services by means of neighboring cell migration based on the received power quality of the target base station, under the premise of service online and ensuring user satisfaction, further reducing the operating energy consumption of the 5G system, thereby realizing the optimization of the energy consumption of the 5G network system. Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for description in the embodiments. Obviously, the drawings described below are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0023] Figure 1 It is the overall flowchart of a 5G base station intelligent shutdown method based on VIP recognition of the present invention.

[0024] Figure 2 It is the comparison chart of the power consumption of RU in the 5G single base station shutdown part between the present invention and other algorithms.

[0025] Figure 3 It is the comparison chart of the traffic statistics of 5G base station clusters between the present invention and other algorithms. Detailed Embodiments

[0026] The following details the embodiments of the present invention. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation of the present invention.

[0027] Embodiment 1.

[0028] A 5G base station intelligent shutdown method based on VIP identification (VDIC, VIPDifferentiation based 5G gNB Intelligently Closing Algorithm) in this embodiment includes the following steps.

[0029] Step S1: VIP cell marking: based on the VIP attributes of users in the base station, base stations without VIP users are screened out and included in the first shutdown candidate set; Step S2: Service quality screening: Perform service quality screening based on the traffic attributes and running time of each service, as well as the signal-to-noise ratio of the cell where it is located, and include low-value service cells into the second shutdown candidate set; Step S3: lightly loaded base station positioning: lightly loaded base stations are positioned according to the real-time load of each base station, and included in the third shutdown candidate set; Step S4: load transfer shutdown: load transfer and shutdown are performed on the base stations in the shutdown candidate set.

[0030] This embodiment can screen out VIP base stations by analyzing the VIP users of each base station; by carefully analyzing each service, it can screen out low-flow services in harsh cell environments; by comprehensively analyzing the average operating time of high-flow services, it can obtain timed high-flow services, and then obtain a list of low-value services; and it can screen out a list of lightly loaded base stations. This embodiment uses differentiated 5G services, based on different important attributes of users and different traffic attributes of services, to comprehensively consider the overall performance of the cell, including coverage performance and quality performance, and conditionally implement user migration between 5G base stations to achieve intelligent shutdown, thereby achieving the goal of optimizing the energy consumption of the 5G network system.

[0031] Embodiment 2.

[0032] A 5G base station intelligent shutdown method based on VIP identification in this embodiment specifically includes the following steps.

[0033] S11: Sum the VIP attributes of all users running in each base station. If the result of the operation is greater than zero, the base station is marked as a VIP base station and cannot be shut down. All non-VIP base stations are included in the first shutdown candidate set. That is, each base station is marked as a VIP cell according to the important attributes of the user, so as to give priority to ensuring that the base station where the VIP user is located is not shut down.

[0034] S21: Calculate the mathematical expectation of the elapsed time of all high-bandwidth services at the current moment for all base stations. Among them, if the traffic attribute of a service is a high-bandwidth service, the counting mark of this service is 1; if the traffic attribute of a service is a low-bandwidth service, the counting mark of this service is 0. Calculate the mathematical expectation based on the counting marks. That is, calculate the mathematical expectation of the elapsed time of all high-bandwidth services at the current moment for a base station according to the traffic attribute and elapsed time of each service in the base station, and then obtain the high-traffic services that have timed out.

[0035] S22: Set the SNR threshold for low-bandwidth services and the SNR threshold for high-bandwidth services, and perform SNR marking on each service in the base station. If the service SNR is less than the SNR threshold for low-bandwidth services, set the SNR mark of this service to 1; if the service SNR is greater than or equal to the SNR threshold for high-bandwidth services, set the SNR mark of this service to 0; if the service SNR is less than the SNR threshold for high-bandwidth services and the elapsed time of this service is greater than or equal to the mathematical expectation, set the SNR mark of this service to 1, otherwise set it to 0. By comprehensively analyzing the SNR and elapsed time of services, filter out low-traffic services in a poor cell environment and high-traffic services that have timed out, so as to perform load transfer and implement shutdown.

[0036] S23: Based on the SNR marks of services, perform SNR marking on each base station to generate a second shutdown candidate set. If the SNR marks of all services running in a base station are 1, set the SNR mark of this base station to 1, otherwise set it to 0; include all base stations with SNR marks of 1 in the second shutdown candidate set, that is, filter out base stations that only contain low-value services.

[0037] By carefully analyzing each service, low-traffic services in a poor cell environment can be filtered out. By comprehensively analyzing the average running duration of high-traffic services, high-traffic services that have timed out can be obtained, and then a list of low-value services can be obtained.

[0038] S31: Set a load threshold, and include all base stations with a load less than the load threshold in the third shutdown candidate set, so as to filter out target base stations with light loads.

[0039] S41: Calculate the intersection of the three shutdown candidate sets, include the base stations that are simultaneously in the three shutdown candidate sets in the target shutdown base station set, and sort them in ascending order according to the reference received power to generate an ascending set; calculate the neighbor cell set of each base station in the ascending set, and remove the cell list belonging to the ascending set from the neighbor cell set to generate a transfer candidate set for the base station.

[0040] By taking the intersection of the first set of candidate base stations to be shut down, the second set of candidate base stations to be shut down, and the third set of candidate base stations to be shut down and arranging them in ascending order, an ascending set of target base stations to be shut down is generated, avoiding shutting down base stations based on a single performance of the service, and achieving a comprehensive consideration of the overall performance of the cell, including coverage performance and quality performance, etc.

[0041] S42: Set a reference received power threshold, select the base stations in the transfer candidate set whose reference received power is not lower than the reference threshold and include them in the target set, and calculate the load margin of each base station in the target set. If the load of the base station to be shut down does not exceed the maximum load margin of the base stations in the target set, perform load transfer and shutdown on the base station to be shut down.

[0042] Based on the received power quality of the target base station, on the premise of ensuring user satisfaction, shut down the 5G base stations for low-value services through the method of neighboring cell migration, so as to optimize the energy consumption of the 5G network system.

[0043] S43: Set an upper limit on the number of base stations to be shut down. After executing step S42, if the number of base stations to be shut down is less than the upper limit on the number of base stations to be shut down, continue to traverse the ascending set until the number of base stations to be shut down reaches the upper limit on the number of base stations to be shut down or the ascending set is traversed.

[0044] Embodiment III.

[0045] A 5G base station intelligent shutdown method based on VIP identification in this embodiment includes u base stations gNB tar ={gNB1, gNB2,..., gNB u}, corresponding loads {cLD1, cLD2,..., cLD u}, corresponding reference received powers {Rsrp1, Rsrp2,..., Rsrp u} (dBm); k k users are running on each base station gNB tar , US v is the i-th user, k，i the VIP attribute LVP of user US k,i ∈{0, 1}; each user conducts k k,i services, SV vw is the j-th service, k,i,j then the services run by user US are SV k,i ={SV k，i , j ∈ (1, 2,..., k k，i，j ; the traffic attribute PSV vw of each service SV k，i，j k，i，j∈ {″B″, ″S″}, where B represents high - bandwidth services and S represents low - bandwidth services; the signal - to - noise ratio of each service is SNR k，i，j , and the elapsed time of each service is YTM k,i,j (s).

[0046] As Figure 1 shown in the overall flowchart of a 5G base - station intelligent shutdown method based on VIP recognition of the present invention. A 5G base - station intelligent shutdown method based on VIP recognition in this embodiment is as follows.

[0047] First, perform VIP cell marking on each base station. For each base station gNB tar ={gNB1, gNB2, …, gNB u} in the set, for each base station gNB k , sum the VIP attributes LVP k,i , i ∈ [1, k v of all users US k，i running on it. If the condition SVP k > 0 is satisfied, it means that the base station gNB k is a VIP base station and cannot be shut down; include all non - VIP base stations in the first shutdown candidate set gNB1 tclose , that is, according to the important attributes of users, perform VIP cell marking on each base station, so as to preferentially ensure that the base stations where VIP users are located are not shut down.

[0048] Then, perform service - quality screening on each base station. Calculate the mathematical expectation YTM tar ={gNB1, gNB2, …, gNB u} of the elapsed time of all high - bandwidth services at the current moment for all base stations gNB now = kΣ k Σ i ∑ j YTM k，i，j / ∑ k，i， j N i，j,k ; where N i，j，k represents the counting mark for service SV k,i,j ; when the condition PSV k,i,j = "B" is satisfied, N i，j，k = 1, and when the condition PSV k，i，j = "S", N i，j，k = 0; that is, calculate the mathematical expectation of the elapsed time of all high - bandwidth services at the current moment of the base station according to the traffic attributes and elapsed time of each service in the base station, and then obtain the high - traffic services that have timed out.

[0049] Set the low-bandwidth service signal-to-noise ratio threshold SNR_S (dBm) and the high-bandwidth service signal-to-noise ratio threshold SNR_B (dBm); for all SNRs that meet the conditions k，i，j The signal-to-noise ratio flag of low-bandwidth services < SNR_S is set to 1, otherwise it is set to 0; for all SNRs that meet the condition k，i，j ≥SNR_B high bandwidth services, its signal-to-noise ratio flag is set to 0. k，i，j <SNR_B, if the business has been carried out for YTM k，i，j ≥YTM now , then set its signal-to-noise ratio flag to 1, otherwise set it to 0. By combining the signal-to-noise ratio and the time of service, low-traffic services in bad cell environments and high-traffic services that have timed out can be screened out, so as to transfer loads and implement shutdown.

[0050] For gNB tar = {gNB1, gNB2, …, gNB u Each base station gNB in k , the signal-to-noise ratio mark of the base station is set to 1 only when the signal-to-noise ratio marks of all services running therein are 1, otherwise it is set to 0; all base stations with signal-to-noise ratio marks of 1 are included in the second shutdown candidate set SNB2 tclose , that is, to filter out base stations that only contain low-value services and avoid shutting down base stations that contain non-low-value services.

[0051] By conducting a detailed analysis of each service, we can screen out low-traffic services in harsh cell environments. By comprehensively analyzing the average operating time of high-traffic services, we can obtain the timed high-traffic services and thus obtain a list of low-value services.

[0052] Then locate the lightly loaded base station. Set the load threshold cLD th ∈[0,1], all cLD that meet the condition k <cLD th The base station is included in the third shutdown candidate set gNB3 tclose , that is, all base stations with loads less than the load threshold are included in the third shutdown candidate set, so as to select target base stations with light loads for load transfer and shutdown.

[0053] Finally, perform load transfer and shutdown. Calculate the neighbor cell set of the base stations in the shutdown candidate set to generate the transfer candidate set of the base stations; set the reference received power threshold, select the base stations in the transfer candidate set whose reference received power is not lower than the reference threshold and include them in the target set, and calculate the load margin of each base station in the target set. If the load of the base station to be shut down does not exceed the maximum load margin of the base stations in the target set, perform load transfer and shutdown on the base station to be shut down. According to the received power quality of the target base station, on the premise of ensuring user satisfaction, shut down the 5G base stations of low-value services through the method of neighbor cell migration, so as to optimize the energy consumption of the 5G network system.

[0054] In a preferred embodiment, the load transfer and shutdown are specifically as follows.

[0055] Calculate the target shutdown base station set ST close = gNB1 tclose ∩gNB2 tclose ∩gNB3 tclose ; Arrange the base stations in the set ST close in ascending order according to the reference received power to obtain the ascending set ST close '; For the first base station gNB close in ST t ', calculate its neighbor cell set gNB t，n , select the cell list gNB close ' that belongs to the ascending set ST t，c in the neighbor cell set, and calculate the transfer candidate set gNBt t of gNB t，x = gNB t,n -gNB t，c .

[0056] Set the reference received power threshold Rsrp th (dBm); Select the gNB t，x that meets the condition Rsrp z ≥Rsrp th in the transfer candidate set gNB z and include it in the target set gNB t，z ; For each base station gNB t，z in gNB z , calculate the load margin ΔcLD z = cLD th -cLD z If the condition ΔcLD z ≥cLD t is met, then transfer the users of the base station gNB t to the gNB z with the maximum load margin, and complete gNB tShutdown of the base station; if there is no base station gNB that meets this condition z , then the shutdown of the base station gNB will not be completed this time t ; In a preferred embodiment, an upper limit Noff for the number of base stations to be shut down is set mx ; after completing the above steps, on the premise that the number of base stations to be shut down does not exceed the upper limit Noff mx , continue to traverse the ascending set ST close ', until the upper limit is reached or ST close ' is traversed completely

[0057] In this embodiment, base stations without VIP users are screened out through the VIP attributes of users, and these base stations are included in the first shutdown candidate set; according to the traffic attributes of each service, the signal-to-noise ratio of the cell where it is located, and the time when the service has been carried out, combined with the signal-to-noise ratio threshold value, base stations with low traffic in poor environmental conditions or high-traffic services that have timed out are screened out and included in the second shutdown candidate set; according to the real-time load of each base station, lightly loaded base stations are screened out, and then the third shutdown candidate set is obtained; calculate the intersection of the above three candidate sets, and finally obtain the target base stations that can be shut down; before shutting down, all users and services of this base station need to be migrated to neighboring cells with a higher reference received power value, and through the estimation of the cell pressure brought by the load migration, the evaluation of the target base station is finally completed. Implement service migration that meets the requirements and shut down the source base station. The shutdown mechanism of the present invention can achieve intelligent shutdown on the premise of ensuring user satisfaction according to the needs of different users and different services, so as to achieve the purpose of energy consumption optimization

[0058] Embodiment 4

[0059] Taking u = 6 as an example, the present invention is specifically described as follows. The base station users and services are shown in Table 1

[0060] Table 1 The basic data is shown in Table 2

[0061] Table 2 Item Data Operating Frequency (GHz) 2.6 Operating Bandwidth (MHz) 100 Total Number of Cell RBs 273 SNR Threshold for Low-Bandwidth Services SNR_S (dBm) -1 SNR Threshold for High-Bandwidth Services SNR_B (dBm) 0 <![CDATA[cLD th > 60％ <![CDATA[Reference received power threshold Rsrp th (dBm)]]> -120 <![CDATA[Upper limit of the number of base stations to be shut down, Noff mx (pcs)]]> 1 A 5G base station intelligent shutdown method based on VIP recognition in this embodiment is specifically as follows

[0062] First, perform VIP cell marking. For each base station gNB tar in gNB k = {gNB1, gNB2..., gNB6}, perform a summation operation on the VIP attributes LVP k，i of all users US v running on it, where i ∈ [1, k k，i , SVP condition is satisfied k VIP base station gNB with >0 k ={gNB1, gNB3, gNB6}, indicating that it cannot be turned off; all non-VIP base stations are included in the first candidate set for shutdown gNB1 tclose ={gNB2, gNB4, gNB5}.

[0063] Then perform service quality screening. For all base stations gNB tar ={gNB1, gNB2…, gNB6}, calculate the mathematical expectation of the already launched time of all high-bandwidth services at the current moment SNR condition is satisfied k，i，j Low-bandwidth services with <SNR_S are {"Service 6", "Service 8", "Service 9", "Service 10"}, and their signal-to-noise ratio marks are set to 1, while those of {"Service 1", "Service 3"} are set to 0; high-bandwidth services that satisfy the condition SNR k，i，j ≥SNR_B are {"Service 2", "Service 5", "Service 11"}, and their signal-to-noise ratio marks are set to 0; high-bandwidth services that satisfy the condition SNR k，i，j <SNR_B and YTM k，i，j ≥YTM now are {"Service 4", "Service 7"}, and their signal-to-noise ratio marks are set to 1. There are no services that satisfy the condition services.

[0064] For each base station gNB in k , the base stations where the signal-to-noise ratio marks of all services running in them are 1 are {gNB4, gNB5}; all base stations with signal-to-noise ratio marks of 1 are included in the second candidate set for shutdown gNB2 tclose ={gNB4, gNB5}.

[0065] Then perform light-load base station positioning. All base stations that satisfy the condition are included in the third candidate set for shutdown

[0066] Finally, perform load transfer and shutdown. Calculate the target set of base stations to be shut down ST ctose =gNB1 tclose ∩gNB2 tclose ∩gNB3 tclose ={gNB4, gNB5}; sort the base stations in the set ST close in ascending order according to the reference received power to obtain the ascending set ST' close ={gNB5, gNB4}.

[0067] For each base station gNB in ST close 't＝5 Calculate its neighbor cell set gNB 5，n ={gNB1, gNB2, gNB3, gNB4, gNB6}, select the cells in the neighbor cell set that belong to the ascending set ST′ close ={gNB5, gNB4} cell list gNB 5，c ={gNB4}, calculate gNB t＝5 transfer candidate set gNB 5，x =gNB 5，n -gNB 5，c ={gNB1, gNB2, gNB3, gNB6}.

[0068] Select in the transfer candidate set gNB 5，x the gNB that satisfies the condition Rsrp z ≥Rsrp th =-120 (dBm) into the target set gNB z ={gNB1, gNB3}; for each base station gNB 5，z in gNB 5，z , calculate the load margin ΔcLD z =cLD z -cLD th ={0.44, 0.33}, both satisfy the condition ΔcLD z ≥cLD z =0.33, then transfer the users of the base station gNB t＝5 to gNB1 with the maximum load margin, and complete the shutdown of the gNB t base station. t＝5

[0069] Since the upper limit of the number of base station shutdowns Noff mx =1, therefore, after completing the shutdown of the gNB t＝5 base station, no further shutdown analysis is performed on the base station gNB4 in the ascending set ST close .

[0070] Simulate the VDIC method of the present invention on the MATLAB platform. The base station clusters composed of 6 5G base stations are mutually configured with neighbor cells, and certain loads are set respectively, so that some RUs (Radio Unit) or DUs (Distributed Unit) of the lightly loaded base stations can be intelligently shut down. The obtained power consumption and traffic statistics are respectively referred to Figure 2 and Figure 3 .

[0071] As Figure 2 ​The figure below shows the power consumption comparison diagram of the present invention and other algorithms for shutting down some RUs in a 5G single base station. During the simulation of a 5G single base station, due to the shutdown of some RUs, the power consumption of the base station will decrease significantly. However, on the premise of ensuring the stable operation of existing services, the power consumption of the base station will be maintained within a relatively stable range. During the simulation of the single base station power consumption, the algorithm performances of VDIC and GSIC are similar.

[0072] As Figure 3 The figure below shows the traffic statistics comparison diagram of the present invention and other algorithms in a 5G base station cluster. During the simulation of the cell cluster traffic, VDIC will give priority to ensuring that the base stations where VIP users are located are not shut down; in a harsh service environment, low-throughput services and high-throughput services with timeouts will be migrated and shut down as much as possible; in a good service environment, VDIC will give priority to retaining the high-throughput services just triggered by users to improve the user experience, so it shows better cell performance than GSIC during the simulation, and also achieves the purpose of reducing power consumption and improving performance.

[0073] A 5G base station intelligent shutdown method based on VIP recognition of the present invention starts from analyzing the important attributes of users, evaluates the traffic attributes of the services carried out by users, combines the signal-to-noise ratio, screens out low-value service cells as target cells to be excluded, and selects target base stations with light loads from them for load transfer and implementation of shutdown. That is, by means of differentiated 5G services, according to the needs of different users for different services, the overall performance of the cell, including coverage performance and quality performance, etc., is comprehensively considered, and conditional user migration between 5G base stations is implemented to achieve intelligent shutdown; it can shut down 5G base stations with low-value services by means of neighbor cell migration on the premise of service online and ensuring user satisfaction according to the received power quality of the target base station, further reducing the operating energy consumption of the 5G system, thus realizing the optimization of the energy consumption of the 5G network system.

[0074] The above are only the preferred embodiments of the present invention, and do not impose any limitations on the present invention. Any simple modifications, changes, and equivalent structural transformations made to the above embodiments according to the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A 5G base station intelligent shutdown method based on VIP recognition, characterized in that, Including: S1: Based on the VIP attributes of users in the base stations, select the base stations without VIP users and include them in the first shutdown candidate set; S2: According to the traffic attributes and the elapsed time of each service, as well as the signal-to-noise ratio of the cell where it is located, perform service quality screening, and include low-value service cells in the second shutdown candidate set; S3: Locate lightly loaded base stations according to the real-time load of each base station and include them in the third shutdown candidate set; S4: Perform load transfer and shutdown on the base stations in the shutdown candidate set.

2. The intelligent shutdown method of a 5G base station based on VIP recognition according to claim 1, wherein, The step S1 includes: performing a summation operation on the VIP attributes of all users running in each base station. If the operation result is greater than zero, mark the base station as a VIP base station and it cannot be shut down, and include all non-VIP base stations in the first shutdown candidate set.

3. The intelligent shutdown method of a 5G base station based on VIP recognition according to claim 1, wherein, The step S2 includes: S21: Calculate the mathematical expectation of the elapsed time of all high-bandwidth services at the current moment of all base stations; S22: Set the signal-to-noise ratio thresholds for low-bandwidth services and high-bandwidth services, and perform signal-to-noise ratio marking on each service in the base station; S23: Based on the signal-to-noise ratio marking of the services, perform signal-to-noise ratio marking on each base station to generate the second shutdown candidate set.

4. The intelligent shutdown method of a 5G base station based on VIP recognition according to claim 3, wherein The step S21 includes: If the traffic attribute of the service is a high-bandwidth service, the count mark of the service is set to 1; if the traffic attribute of the service is a low-bandwidth service, the count mark of the service is set to 0; calculate the mathematical expectation based on the count mark.

5. A 5G base station intelligent shutdown method based on VIP recognition according to claim 3 or 4, characterized in that, The step S22 includes: If the service signal-to-noise ratio is less than the low-bandwidth service signal-to-noise ratio threshold, set the signal-to-noise ratio mark of the service to 1; If the service signal-to-noise ratio is greater than or equal to the high-bandwidth service signal-to-noise ratio threshold, set the signal-to-noise ratio mark of the service to 0; If the service signal-to-noise ratio is less than the high-bandwidth service signal-to-noise ratio threshold and the elapsed time of the service is greater than or equal to the mathematical expectation, set the signal-to-noise ratio mark of the service to 1, otherwise set it to 0.

6. The intelligent shutdown method of a 5G base station based on VIP recognition according to claim 5, wherein, The step S23 includes: If the signal-to-noise ratio marks of all services running in the base station are all 1, set the signal-to-noise ratio mark of the base station to 1, otherwise set it to 0; include all base stations with signal-to-noise ratio marks of 1 in the second shutdown candidate set.

7. A 5G base station intelligent shutdown method based on VIP recognition according to claim 1, characterized in that The step S3 includes: Set a load threshold, and include all base stations with a load less than the load threshold in the third shutdown candidate set.

8. The intelligent shutdown method of a 5G base station based on VIP recognition according to claim 1 or 7, characterized in that, The step S4 includes: S41: Calculate the neighbor cell set of the base stations in the shutdown candidate set to generate a transfer candidate set of the base stations; S42: Set a reference received power threshold, select the base stations with a reference received power not lower than the reference threshold in the transfer candidate set and include them in the target set, and calculate the load margin of each base station in the target set. If the load of the base station to be shut down does not exceed the maximum load margin of the base stations in the target set, perform load transfer and shutdown on the base station to be shut down.

9. The intelligent shutdown method of a 5G base station based on VIP recognition according to claim 8, characterized in that, The step S41 specifically includes: Calculate the intersection of the three shutdown candidate sets, include the base stations that are simultaneously in the three shutdown candidate sets in the target shutdown base station set, and sort them in ascending order according to the reference received power to generate an ascending set; Calculate the neighbor cell set of each base station in the ascending set, and remove the cell list belonging to the ascending set in the neighbor cell set to generate a transfer candidate set of the base stations.

10. The intelligent shutdown method of a 5G base station based on VIP recognition according to claim 9, characterized in that, The step S4 also includes: S43: Set the upper limit of the number of base stations to be shut down. After performing step S42, if the number of base stations to be shut down is less than the upper limit of the number of base stations to be shut down, continue to traverse the ascending set until the number of base stations to be shut down reaches the upper limit of the number of base stations to be shut down or the ascending set is traversed completely.

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