5G Base Station Intelligent Sleep and Wake-up Energy Saving Method Based on Edge Computing

Abstract

The present invention relates to the field of information and communication technologies, and particularly to an intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing, which is applied to competing base stations and arbitration base stations in a distributed base station cluster. The competing base stations judge whether to participate in the competition based on service load, channel quality, and energy consumption information, and broadcast competition information to the distributed base station cluster. After receiving the competition information, the arbitration base stations search for alternative base stations with similar historical service patterns within their arbitration areas, sort the base stations according to the idle load, and decide whether to vote in support of the corresponding competing base stations based on the sequence positions of the alternative base stations. After each arbitration base station votes, the competing base station with the most votes is summarized as the serving base station and broadcast to the base station cluster to adjust the operating state of the base stations. It effectively reduces unnecessary wake-up and energy consumption of the base stations, improves the energy efficiency of the 5G network, ensures service quality, and realizes intelligent energy-saving optimization.

Description

Technical Field

[0001] The present invention relates to the field of information and communication technologies, and particularly to an intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing. Background Art

[0002] With the wide deployment of 5G networks, mobile communication operators are facing unprecedented energy consumption challenges. Since 5G base stations adopt large-scale antenna arrays, millimeter-wave communications, and higher spectral bandwidths, the power consumption per unit base station is much higher than that of traditional 4G base stations. Actual tests show that the single-station power consumption of 5G base stations is about 3-4 times that of 4G base stations, and even reaches 3.7-3.9 kW under full load, resulting in a significant increase in the proportion of the power expenditure of the communication network in the operating cost (OPEX) of the operator.

[0003] For example, the Chinese patent application with the publication number CN115604793A provides a method and system for waking up a sleeping base station. The method includes: the base station receives a signal to be detected in the sleeping state and determines the signal-to-interference-plus-noise ratio of the signal to be detected; wherein, the base station receiver is turned on in the sleeping state; based on the signal-to-interference-plus-noise ratio of the signal to be detected, it is determined that the base station receives a signal sent by a user, and the base station is switched to the wake-up state. It can accurately identify whether the signal received by the sleeping base station is a signal sent by a user, reduce the influence of interference and noise on the recognition result, and wake up the sleeping base station in time when it is determined that a signal sent by a user is received.

[0004] The above existing technologies all have the problems raised in this background art: inefficient resource allocation leads to frequent state switching of some base stations, increasing additional energy consumption. To solve the above problems, this application designs an intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing in view of the deficiencies of the prior art. The method is applied to competing base stations and arbitration base stations in a distributed base station cluster. The competing base stations judge whether to participate in the competition based on service load, channel quality, and energy consumption information, and broadcast competition information to the distributed base station cluster. After receiving the competition information, the arbitration base stations search for alternative base stations with similar historical service patterns within their arbitration areas, sort the base stations according to the idle load, and decide whether to vote to support the corresponding competing base stations based on the sequence positions of the alternative base stations. After each arbitration base station votes, the competing base station with the most votes is summarized as the serving base station and broadcast to the base station cluster to adjust the operating state of the base stations. It effectively reduces unnecessary wake-up and energy consumption of the base stations, improves the energy efficiency of the 5G network, ensures service quality, and realizes intelligent energy-saving optimization.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A 5G base station intelligent sleep and wake-up energy-saving method based on edge computing is applied to competing base stations in a distributed base station cluster. The distributed base station cluster further includes multiple arbitration base stations, and each arbitration base station is one of the base stations in the distributed base station cluster that are not currently participating in the competition. Each arbitration base station corresponds to an arbitration area composed of multiple base stations. Each base station is configured with an edge computing node. The 5G base station intelligent sleep and wake-up energy-saving method includes:

[0008] Receiving a network response request of a user terminal broadcast by the distributed base station cluster;

[0009] Generating competition information according to competition metrics, and broadcasting the competition information and historical processing information to the distributed base station cluster, so that each arbitration base station votes for a serving base station based on the received competition information and historical processing information of the competing base stations;

[0010] If the competing base station is selected as the serving base station, switch its own state to or maintain the wake-up state.

[0011] The competition metrics include service load, channel quality, and base station energy consumption. Generating competition information according to the competition metrics includes:

[0012] Obtaining the current service load, where the current service load includes PRB occupancy rate, number of user connections, and throughput, and calculating the service load index according to a preset weight;

[0013] Obtaining channel quality metrics, where the channel quality metrics include RSRP, SINR, and path loss, and calculating the channel quality level according to a channel quality threshold;

[0014] Obtaining the current power consumption, energy efficiency per bit, and switching energy consumption overhead, and calculating the base station energy consumption index;

[0015] Judging whether it is necessary to compete for the network response request according to the service load index, channel quality level, and base station energy consumption index. If necessary, construct competition information. If not, broadcast the base station identification information to the distributed base station cluster to serve as an arbitration base station.

[0016] Judging whether it is necessary to compete for the network response request according to the service load index, channel quality level, and base station energy consumption index includes:

[0017] Comparing the service load index with a first threshold to judge whether the current base station service load is higher than the first threshold, where the first threshold is adjusted by the edge computing node according to historical load data;

[0018] If the service load index is higher than the first threshold, it is determined that it is necessary to compete for the response request;

[0019] If the service load index is less than or equal to the first threshold, further compare the channel quality level with a second threshold. When the channel quality level is greater than or equal to the second threshold, further compare the base station energy consumption index with a third threshold; otherwise, abandon the competition, where the second threshold is determined by all arbitration base stations in the previous round based on the average received signal quality reported by the user terminal.

[0020] If the base station energy consumption index is less than the third threshold, it is determined that the response request needs to be competed for; otherwise, abandon the competition.

[0021] A 5G base station intelligent sleep and wake-up energy-saving method based on edge computing is applied to an arbitration base station in a distributed base station cluster. Each arbitration base station corresponds to an arbitration area composed of multiple base stations. The distributed base station cluster further includes multiple competing base stations. Each arbitration base station is one of the base stations in the distributed base station cluster that are not currently participating in the competition. Each base station is configured with an edge computing node. The 5G base station intelligent sleep and wake-up energy-saving method includes:

[0022] Receive the competition information and historical processing information sent by each competing base station that is not within its own arbitration area.

[0023] Vote for a serving base station according to the competition information and historical processing information corresponding to each competing base station.

[0024] Broadcast the base station identifier of the serving base station to the distributed base station cluster, so that the corresponding competing base stations can switch or maintain their own states to the wake-up state.

[0025] The voting for a serving base station according to the competition information and historical processing information corresponding to each competing base station includes:

[0026] For each competing base station, determine whether there is a corresponding alternative base station within its own arbitration area according to the competition information and historical processing information corresponding to each competing base station.

[0027] Sort all the base stations within the own arbitration area in descending order of idle load to obtain an idle load sequence.

[0028] For each competing base station with an alternative base station, determine the sequence position of the corresponding alternative base station. If the sequence position of the corresponding alternative base station is after a set position, confirm to vote for this competing base station.

[0029] Receive the voting votes of each competing base station sent by other arbitration base stations, and combine with the voting votes of each competing node determined by itself to summarize and determine the serving base station.

[0030] The determination of whether there is a corresponding alternative base station within the own arbitration area includes:

[0031] Calculate the similarity between the competing base station and the historical processing information of each base station within its own arbitration area according to the historical processing information of the competing base stations;

[0032] Select the base station with the highest similarity to the historical processing information of each competing base station within its own arbitration area as the corresponding replacement base station according to the similarity.

[0033] The summarizing and determining the serving base station includes:

[0034] Each arbitration base station generates voting information according to the voting result determined by itself, and the voting information includes the identifiers of the competing base stations that obtain the vote of the arbitration base station;

[0035] Broadcast its own voting information to the distributed base station cluster;

[0036] Receive the voting information broadcast by other arbitration base stations, and combine with its own voting information to count the number of votes obtained by each competing base station;

[0037] Take the competing base station with the most votes as the serving base station.

[0038] When multiple competing base stations obtain the same maximum number of votes, the summarizing and determining the serving base station further includes:

[0039] Obtain the service load index, channel quality level, and base station energy consumption index in the competition information;

[0040] Successively execute the preference rules until a unique serving base station is determined.

[0041] The successively executing the preference rules until a unique serving base station is determined includes:

[0042] Compare the service load indexes of the competing base stations with the same number of votes, and select the base station with the highest service load index as the serving base station;

[0043] If the service load indexes are the same, then compare the channel quality levels, and select the base station with the highest channel quality level as the serving base station;

[0044] If the channel quality levels are the same, then compare the base station energy consumption indexes, and select the base station with the lowest base station energy consumption index as the serving base station;

[0045] If the base station energy consumption indexes are the same, then select the base station with the highest historical user connection success rate as the serving base station;

[0046] If the historical user connection success rates are the same, then select the base station with the shortest response delay from the last wake-up from the dormant state to the active state as the serving base station.

[0047] When the number of arbitration base stations does not meet the preset base threshold, the 5G base station intelligent sleep and wake-up energy-saving method further includes:

[0048] According to the competition information of each competing base station, perform reverse sorting on the competition information to generate a reverse list;

[0049] Sequentially convert the competing base stations in the reverse list into arbitration base stations in order until the number of arbitration base stations meets the preset base threshold.

[0050] Compared with the prior art, the beneficial effects of the present invention are:

[0051] Based on the similarity of historical service models, the present invention matches corresponding alternative base stations for each competing base station within the arbitration area, and determines whether to vote in support of the competing base station by combining the idle load sorting position of the alternative base stations. Compared with the traditional arbitration method that only relies on static competition information, the present invention can more accurately evaluate the adaptability of competing base stations to the services in the arbitration area, ensuring that the selected serving base stations can not only meet the service requirements but also optimize resource scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent:

[0053] Figure 1 It is a schematic flowchart of the edge-computing-based 5G base station intelligent sleep and wake-up energy-saving method applied to competing base stations in Embodiment 1 of the present invention;

[0054] Figure 2 It is a schematic flowchart of the edge-computing-based 5G base station intelligent sleep and wake-up energy-saving method applied to arbitration base stations in Embodiment 2 of the present invention;

[0055] Figure 3 It is a schematic diagram of the arbitration area in Embodiment 2 of the present invention;

[0056] Figure 4 It is a schematic diagram of arbitration voting in Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0058] Embodiment 1

[0059] Please refer to Figure 1, an embodiment provided by the present invention: A 5G base station intelligent sleep and wake-up energy-saving method based on edge computing applied to competing base stations, which is applied to competing base stations in a distributed base station cluster. The distributed base station cluster further includes multiple arbitration base stations. Each arbitration base station is one of the base stations in the distributed base station cluster that are not currently participating in the competition. Each arbitration base station corresponds to an arbitration area composed of multiple base stations. Each base station is configured with an edge computing node. The 5G base station intelligent sleep and wake-up energy-saving method includes:

[0060] S1: Receive the network response request of the user terminal broadcast by the distributed base station cluster;

[0061] In this embodiment, each competing base station periodically listens to the network status broadcast of the distributed base station cluster, which includes the network response request of the user terminal. This network response request can be a service connection request initiated by the user, such as an uplink or downlink data request, or a service optimization signaling sent by the network itself, such as an adjustment request triggered by the network side detecting a sudden increase in local traffic.

[0062] Specifically, each competing base station can timely obtain the current network status and provide a basis for subsequent competition decisions, ensuring that the selected serving base station can meet the user's needs and avoiding unnecessary base station wake-up or sleep failure. Compared with the traditional fixed time interval strategy, it can more accurately reflect the actual situation of network load and improve the scheduling efficiency of network resources.

[0063] S2: Generate competition information according to competition metrics;

[0064] In this embodiment, after each competing base station receives the network response request, it will calculate the competition information based on competition metrics such as the current service load, channel quality, and base station energy consumption, and establish a fair competition mechanism among multiple base stations to ensure that among multiple candidate base stations, a base station with strong service carrying capacity, good channel quality, and low energy consumption can be selected to provide services. Compared with the traditional method of making decisions only based on service load or channel quality alone, it comprehensively considers three factors: load balancing, signal coverage, and energy saving, which can effectively improve the scientificity of resource scheduling and reduce energy consumption at the same time.

[0065] S3: Broadcast the competition information and historical processing information to the distributed base station cluster so that each arbitration base station can vote for the serving base station based on the received competition information and historical processing information of the competing base station;

[0066] In this embodiment, after the competing base station generates the competition information, it will broadcast it together with the historical processing information to the distributed base station cluster for the arbitration base station to vote. The historical processing information mainly includes:

[0067] Historical user connection success rate: Measuring the stability of the base station in providing services in the past;

[0068] Historical average throughput: used to evaluate the bearing capacity of the base station under high traffic load;

[0069] Historical channel quality fluctuation: reflecting the long-term stability of the base station channel environment.

[0070] Furthermore, after receiving the competition information and historical processing information of all competing base stations, the arbitration base station selects the serving base station by voting based on the intelligent voting mechanism. The voting process includes:

[0071] Calculate the similarity of the historical processing information between the competing base station and the base stations within its arbitration area, and select the base station with the highest similarity as the replacement base station.

[0072] Sort according to the idle load from large to small, and decide whether to vote for the competing base station according to the ranking position of the replacement base station.

[0073] After completing the independent voting, the voting result will be broadcast to the entire base station cluster, and finally the competing base station with the most votes will be determined as the final serving base station.

[0074] S4: If selected as the serving base station, switch or maintain its own state to the wake-up state;

[0075] In this embodiment, the selected serving base station will perform a state switch, including waking up from the sleep state and maintaining the current wake-up state, which is specifically determined according to whether the base station is active. For other unselected competing base stations, only maintain their current state, avoiding the long-term high energy consumption problem caused by the traditional fixed operation mode of the base station, and also preventing unnecessary wake-up operations, improving the overall energy efficiency of the base station.

[0076] The specific steps of S2 are as follows:

[0077] S2.1: Obtain the current traffic load, where the current traffic load includes PRB occupancy, number of user connections, and throughput, and calculate the traffic load index according to the preset weight;

[0078] Specifically, in different scenarios, the measurement criteria for traffic load should be different. Relying solely on a certain indicator (such as PRB occupancy) is prone to misjudgment. For example, in some scenarios, although the PRB occupancy is high, the number of user connections is small, indicating that the resource utilization efficiency of the base station is low and should not be directly regarded as high load. Therefore, by calculating the traffic load index through weighting, the actual traffic pressure of the base station can be more comprehensively reflected, providing a more reasonable basis for competition decision-making.

[0079] In this embodiment, the competing base stations need to first obtain the current traffic load information in order to determine their own network resource usage and calculate the traffic load index. The traffic load information includes the PRB (Physical Resource Block) occupancy rate, the number of user connections, and the throughput. Among them, the PRB occupancy rate reflects the usage of the available radio resources of the base station, the number of user connections represents the number of users served by the current base station, and the throughput measures the overall data processing ability of the base station.

[0080] Furthermore, the base station will perform a weighted sum of these three key parameters according to the preset weights to generate the traffic load index. The setting of the weights is dynamically adjusted based on factors such as the base station's historical traffic patterns, geographical location, and service type. For example, for base stations in hotspots, the throughput weight is relatively high, while for base stations with a wide coverage but few connected users, the weight of the PRB occupancy rate is relatively high.

[0081] S2.2: Obtain the channel quality indicators, where the channel quality indicators include RSRP, SINR, and path loss, and calculate the channel quality level according to the channel quality threshold;

[0082] Specifically, relying solely on a single channel quality parameter (such as RSRP) may not accurately reflect the communication ability of the base station. For example, in a dense cell deployment environment, the RSRP may be relatively high, but due to severe interference from neighboring cells, the SINR may be relatively low, resulting in poor actual communication quality. Therefore, by comprehensively considering multiple channel quality indicators and combining them with the channel quality threshold for grading, the service ability of the base station can be more accurately reflected, thus avoiding selecting a base station with poor channel quality as the serving base station and improving the overall network performance.

[0083] In this embodiment, the base station first obtains its own RSRP and SINR through a periodic measurement and reporting mechanism. Among them, RSRP is used to measure the received power of the reference signal sent by the base station at the user end, and SINR is used to measure the interference situation of the wireless channel. The base station will also combine the path loss model (based on the wireless propagation environment, such as urban, suburban, or indoor scenarios) to calculate the overall channel attenuation situation. Smooth the multiple measurement values over a period of time to ensure the stability of the channel quality assessment.

[0084] Furthermore, when calculating the channel quality level, the base station will compare the measured RSRP, SINR, and path loss with the preset channel quality threshold to determine the channel quality level.

[0085] The base station matches the RSRP value with the preset RSRP threshold table to determine the RSRP level:

[0086] RSRP > -80 dBm, denoted as RSRP_Rank = 5 (excellent);

[0087] -90 dBm ≤ RSRP ≤ -80 dBm, denoted as RSRP_Rank = 4 (good);

[0088] -100 dBm ≤ RSRP ≤ -90 dBm, denoted as RSRP_Rank = 3 (average);

[0089] -110 dBm ≤ RSRP ≤ -100 dBm, denoted as RSRP_Rank = 2 (poor);

[0090] RSRP < -110 dBm, denoted as RSRP_Rank = 1 (extremely poor).

[0091] The base station matches the SINR value with the preset SINR threshold table to determine the SINR rank:

[0092] SINR > 20 dB, denoted as SINR_Rank = 5 (excellent);

[0093] 10 dB ≤ SINR ≤ 20 dB, denoted as SINR_Rank = 4 (good);

[0094] 5 dB ≤ SINR ≤ 10 dB, denoted as SINR_Rank = 3 (average);

[0095] 0 dB ≤ SINR ≤ 5 dB, denoted as SINR_Rank = 2 (poor);

[0096] SINR < 0 dB, denoted as SINR_Rank = 1 (extremely poor).

[0097] After the base station calculates the path loss, it matches with the preset path loss threshold table:

[0098] Path loss < 90 dB, denoted as Path_loss_Rank = 5 (excellent);

[0099] 90 dB ≤ Path loss ≤ 100 dB, denoted as Path_loss_Rank = 4 (good);

[0100] 100 dB ≤ Path loss ≤ 110 dB, denoted as Path_loss_Rank = 3 (average);

[0101] 110 dB ≤ Path loss ≤ 120 dB, denoted as Path_loss_Rank = 2 (poor);

[0102] Path loss > 120 dB, denoted as Path loss _ level = 1 (extremely poor).

[0103] Furthermore, based on the weighted calculation method, the RSRP _ level, SINR _ level, and Path loss _ level are weighted and summed to calculate the final channel quality level.

[0104] S2.3: Obtain the current power consumption, energy efficiency per bit, and switching energy consumption overhead, and calculate the base station energy consumption index;

[0105] In this embodiment, competing base stations need to evaluate their own energy consumption situations in order to select a base station with relatively high energy efficiency as the serving base station while ensuring service quality. The energy consumption calculation of the base station mainly involves three aspects: current power consumption, energy efficiency per bit, and switching energy consumption overhead.

[0106] Furthermore, the current power consumption of the base station is comprehensively determined by the power consumption of components such as the power amplifier (PA), baseband processing unit (BBU), and cooling system of the base station, and is usually measured in real time through a built-in power management module.

[0107] Furthermore, the energy efficiency per bit is an indicator to measure the energy efficiency of the base station. The calculation method is the ratio of the total throughput of the base station to the total power consumption within a unit time. The higher this value, the more data the base station can transmit under unit power consumption, and the higher the energy efficiency. Through the adaptive energy efficiency analysis algorithm, combined with historical service data, the current energy efficiency per bit is calculated to determine whether it has the ability of efficient energy consumption management.

[0108] Furthermore, the switching energy consumption overhead mainly refers to the energy loss during the process of the base station waking up from the sleep state to the normal working state. The base station predicts whether its energy consumption meets the energy-saving optimization goal if it is selected as the serving base station currently by statistically analyzing the average power consumption and wake-up time of the recent several wake-up operations.

[0109] S2.4: Determine whether to compete for the network response request according to the service load index, channel quality level, and base station energy consumption index. If needed, construct competition information. If not, broadcast the base station identification information to the distributed base station cluster to serve as an arbitration base station;

[0110] In this embodiment, after obtaining the service load index, channel quality level, and base station energy consumption index, the competing base station needs to comprehensively judge whether it is suitable to compete for the network response request, and construct competition information or become an arbitration base station according to the decision result. The competition information includes the service load index, channel quality level, and base station energy consumption index. The construction method of the competition information adopts a standardized coding format to reduce the amount of broadcast data and improve the information transmission efficiency. In addition, the competition information will be protected by a security mechanism to prevent information tampering and improve the security and reliability of the system.

[0111] Furthermore, the arbitration base station is randomly selected and dynamically adjusted according to a preset base threshold.

[0112] Specifically, after the competition decision is completed, the base stations that did not participate in the competition will be randomly selected as arbitration base stations. The number of selected base stations is restricted by the base threshold to ensure that the number of arbitration base stations can meet the voting requirements. The minimum number of the base threshold is set by the arbitration mechanism in the distributed base station cluster and is usually adjusted based on historical network data. If the number of arbitration base stations is insufficient, they will be supplemented from the competing base stations in the order of the lowest service load priority.

[0113] The specific steps of S2.4 are as follows:

[0114] S2.4.1: Compare the service load index with the first threshold to determine whether the current base station's service load is higher than the first threshold, where the first threshold is adjusted by the edge computing node according to historical load data;

[0115] In this embodiment, after each competing base station receives a network response request from a user terminal, it first needs to evaluate its own service load level to determine whether there are sufficient resources to participate in the competition. The service load index is an important parameter for measuring the current resource usage of the base station, and its calculation is based on key indicators such as PRB (Physical Resource Block) occupancy rate, number of user connections, and throughput. To make the judgment of the service load index more accurate, the base station does not use a fixed threshold value, but dynamically adjusts it based on historical load data, and the edge computing node is responsible for calculating the first threshold.

[0116] Specifically, the edge computing node will regularly count the historical load situation of the base station, including the average service load index within a certain past time window and the load situations of other base stations in the same geographical area, to ensure that the first threshold can adapt to different service models.

[0117] Exemplarily, during peak hours, the edge computing node will increase the first threshold to ensure that only truly high-load base stations participate in the competition; while during low-traffic hours, it will decrease the first threshold to encourage more base stations to participate in the competition and improve network resource utilization. Adapt to different traffic scenarios, avoid the competition imbalance problem caused by the fixed threshold strategy, reduce unnecessary competition, and optimize the overall network energy efficiency.

[0118] S2.4.2: If the service load index is higher than the first threshold, it is determined that the response request needs to be competed for;

[0119] In this embodiment, if the service load index exceeds the first threshold, it indicates that the base station has a strong service carrying capacity and a large traffic demand. Therefore, this base station should actively compete to become the serving base station. In this case, the base station will immediately construct competition information and broadcast it to the distributed base station cluster to participate in the selection process of the serving base station. The competition information includes key parameters such as the current service load index, channel quality level, and base station energy consumption index of the base station for the arbitration base station to evaluate. Ensure that high-load base stations participate first, so as to ensure that service requirements are met in a timely manner, reduce resource waste, and improve the overall service capacity of the 5G network. In addition, by preferentially selecting high-service-load base stations as competitors, the utilization rate of spectrum resources can also be improved, the energy consumption overhead of low-load base stations can be reduced, and the network can still maintain a high operating efficiency under high-load conditions.

[0120] S2.4.3: If the service load index is less than or equal to the first threshold, further compare the channel quality level with a second threshold. When the channel quality level is greater than or equal to the second threshold, further compare the base station energy consumption index with a third threshold; otherwise, abandon the competition, where the second threshold is determined by all arbitration base stations in the previous round based on the average received signal quality reported by user terminals.

[0121] In this embodiment, if the service load index of the base station does not exceed the first threshold, it does not mean that the base station must be unable to compete. Instead, it is necessary to further evaluate whether the channel quality is excellent enough. The arbitration base stations in the previous round calculate based on the received signal quality reported by all user terminals to determine the second threshold in the current environment.

[0122] Exemplarily, in an environment with strong wireless interference, the arbitration base station will increase the second threshold to ensure that only base stations with excellent channel quality can participate in the competition; while in an environment with relatively abundant wireless resources, the second threshold is appropriately reduced to encourage more base stations to compete and improve the network coverage ability.

[0123] Specifically, after receiving the second threshold, the base station will compare its own channel quality level with this threshold. If its channel quality level is greater than or equal to the second threshold, the base station still has the qualification to compete and enters the next energy consumption screening; otherwise, the base station will abandon the competition and turn to the candidate sequence of the arbitration base station. Ensure that the selected serving base station has good wireless channel quality, thereby improving the user experience, reducing network congestion and disconnection risks. Make the network resource allocation more reasonable and improve the overall communication performance.

[0124] S2.4.4: If the base station energy consumption index is less than the third threshold, it is determined that the response request needs to be competed for; otherwise, abandon the competition;

[0125] In this embodiment, if the traffic load index of the base station is less than or equal to the first threshold, but the channel quality level is higher than the second threshold, the power consumption situation of the base station needs to be considered to ensure the energy saving of network operation.

[0126] Specifically, the current power consumption reflects the current operating energy consumption of the base station, the energy efficiency per bit measures the traffic transmission capacity of the base station under unit energy consumption, and the switching energy consumption overhead evaluates the additional energy consumption of the base station from dormancy to operation. The base station will compare the calculated energy consumption index with the third threshold, which is set by analyzing historical energy consumption data and the characteristics of the base station equipment.

[0127] Exemplarily, for remote base stations with weak power grid supply capacity, the third threshold is set relatively low to limit the frequent wake-up of high-energy-consuming base stations; while for base stations in urban areas, due to sufficient power resources, the third threshold is set relatively high to give priority to traffic demands.

[0128] Furthermore, when the energy consumption index of the base station is lower than the third threshold, it indicates that the base station has high energy efficiency, so it can participate in the competition and broadcast competition information; on the contrary, if the energy consumption index of the base station is greater than or equal to the third threshold, even if the traffic load and channel quality meet the requirements, it will not participate in the competition, but choose to give up the competition and turn into an arbitration base station. This screening mechanism ensures finding the best balance between traffic demands and energy efficiency, avoiding increased power consumption due to the frequent competition of high-energy-consuming base stations, while ensuring the network service quality. It adapts to different power supply situations, improves the energy saving effect of 5G base stations, reduces the operation cost, and realizes more efficient base station resource scheduling.

[0129] Embodiment 2

[0130] Please refer to Figure 2 , the present invention provides an embodiment: an edge computing-based 5G base station intelligent sleep and wake-up energy saving method applied to an arbitration base station, which is applied to an arbitration base station in a distributed base station cluster. Each arbitration base station corresponds to an arbitration area composed of multiple base stations. The distributed base station cluster further includes multiple competing base stations. Each arbitration base station is one of the base stations that are currently not participating in the competition in the distributed base station cluster. Each base station is configured with an edge computing node. The specific steps of the 5G base station intelligent sleep and wake-up energy saving method are as follows:

[0131] A1: Receive the competition information and historical processing information sent by each competing base station that is not within its own arbitration area;

[0132] In this embodiment, after each arbitration base station enters the arbitration state, it will listen to and receive the competition information and historical processing information sent by all competing base stations within its non-arbitration area. The competition information includes the service load index, channel quality level, and base station energy consumption index, which are used to measure the current operating state and service capabilities of the competing base stations; the historical processing information includes past service records, historical user connection success rate, and historical average throughput, which are used to evaluate the long-term stability and reliability of the competing base stations.

[0133] A2: Vote for the serving base station according to the competition information and historical processing information corresponding to each competing base station;

[0134] In this embodiment, after the arbitration base station receives the competition information and historical processing information of the competing base stations, it will select the optimal serving base station based on an intelligent voting mechanism. The voting process includes multiple stages to ensure that the finally selected base station can not only meet the service requirements but also achieve the energy-saving goal. Compared with the traditional fixed strategy, this application can adapt to different network load conditions. Through historical information analysis + intelligent sorting and voting, the selected serving base station can not only meet the service requirements but also effectively save energy. The introduction of the alternative base station strategy can reduce unnecessary base station wake-up, thereby further reducing the overall network energy consumption and improving the energy-saving efficiency of the 5G network.

[0135] A3: Broadcast the base station identifier of the serving base station to the distributed base station cluster so that the corresponding competing base stations can switch or maintain their states to the wake-up state;

[0136] In this embodiment, after the arbitration base station completes the voting, it will broadcast the identifier of the finally selected serving base station to the entire distributed base station cluster to notify all competing base stations of the voting result. For the selected serving base station, it will switch or maintain the wake-up state to continue providing services to users, while the unselected competing base stations will maintain their current states. To ensure the smoothness of the base station state switch, the broadcast voting result also includes a load transfer strategy to ensure that users can seamlessly migrate to the target base station during the base station switch. For example, if a base station switches from the dormant state to the active state, the surrounding cells will adjust the load balancing parameters to migrate some user traffic to this base station to make full use of its resources and improve the overall network efficiency. In addition, during the broadcast process, the arbitration base station will adopt a differential broadcast mechanism to send the status change information only to the affected base stations instead of broadcasting it to the entire network, thereby reducing the communication overhead and improving the network efficiency.

[0137] Specifically, although the existing technology can perform simple voting through the static information reported by the competing base stations to achieve the sleep and wake-up decisions of 5G base stations, there are still obvious deficiencies in practical applications. For example, after receiving information from competing base stations outside the area, the existing arbitration base stations often lack effective means to evaluate the necessity of the competing base stations in actual business scenarios, especially unable to accurately judge whether the base stations outside the area can solve the actual business carrying needs in the arbitration area, resulting in incorrect voting decisions when the business load fluctuates greatly or resources are tight. This method is not only prone to unreasonable allocation of base station resources, but also causes base stations to wake up and sleep frequently, seriously affecting network energy efficiency and service quality.

[0138] Furthermore, in this embodiment, an intelligent voting method based on "position of the idle load sequence of the replacement base station" is proposed to solve the above problem. Specifically, when the arbitration base station votes, the historical processing information and competition information are first used to find a replacement base station with similar historical business performance inside the arbitration area for each competing base station outside the area; then, according to the current position of the replacement base station in the idle load sequence of base stations in the area, it is decided whether to vote for the corresponding competing base station. For example, when the historical processing information of a competing base station A is highly similar to that of base station B in the arbitration area, base station B will be selected as a replacement base station for base station A. After the arbitration base station sorts the idle loads of all base stations in the area, if the idle load of the replacement base station B ranks low (that is, the resources of the replacement base station itself are relatively tight or busy), it means that if the competing base station A is selected as the service base station, it can effectively alleviate the business load pressure in the area, so it is confirmed to vote for the competing base station A; on the contrary, if the idle load of the replacement base station B ranks high (that is, the idle resources of the replacement base station itself are relatively sufficient), it means that the existing base stations inside the arbitration area are sufficient to bear the business needs of the area, and there is no need to introduce additional external competing base stations to share the business, so the voting for the competing base station A is not performed.

[0139] See also Figure 3 and Figure 4, Exemplarily, assume that there is a business peak in a certain arbitration area currently, and there are competing base stations X and Y outside the area participating in the competition. Since the traditional arbitration method only votes based on the static indicators of the base stations, it may wrongly ignore the actual service value of base stations X and Y, or wrongly select an inappropriate base station to wake up. In this embodiment, the arbitration base station first determines the base station M most similar to base station X and the base station N most similar to base station Y in the area as substitute base stations according to historical data, and then analyzes the idle load ranking of base stations N and M. If the ranking of base station N in the idle load sequence in the area is after the set position, it indicates that the existing base station resources in this area are in short supply. If base station X is selected, the business pressure can be effectively shared. Therefore, the arbitration base station confirms to vote for competing base station X. On the contrary, if the idle load ranking of substitute base station M is before the set position, it means that there are sufficient base station resources in this area to meet the business requirements. At this time, the participation of base station Y in service will not bring obvious benefits, but will cause additional energy consumption. Therefore, the arbitration base station will reasonably give up voting for base station Y.

[0140] Obviously, the method based on the position of the idle load sequence of the substitute base station proposed in this embodiment effectively solves the technical defect that the existing technology's arbitration decision only relies on static competition information and cannot accurately evaluate the business adaptability of base stations outside the area. Through this method, the arbitration base station can accurately judge the actual value of the participation of base stations outside the area in the business bearing in the area, so as to precisely control the wake-up and sleep behaviors of the base stations, avoid resource waste and energy consumption increase, and effectively improve the network service quality and energy efficiency level.

[0141] The specific steps of A2 are as follows:

[0142] A2.1: For each competing base station, determine whether there is a corresponding substitute base station in its own arbitration area according to the competition information and historical processing information corresponding to each competing base station;

[0143] In this embodiment, since the competing base station itself is located outside the area, it is difficult for the arbitration base station to directly judge the actual performance of its service ability in this area. By finding substitute base stations similar to the historical data, the true business performance of the competing base station can be effectively inferred, so as to more accurately judge whether the business in this area should be assigned to the competing base station, and improve the accuracy and rationality of the selection of the serving base station.

[0144] Specifically, the arbitration base station first obtains the historical processing information provided by the competing base station, including but not limited to key indicators such as the business processing mode, user connection success rate, network load trend, and response delay in the past period of time;

[0145] Furthermore, the arbitration base station utilizes the historical service data of all base stations within its own area stored in its edge computing nodes, and through intelligent analysis methods, such as cosine similarity, Euclidean distance, or other multi-dimensional data similarity analysis methods, calculates the similarity between the competing base station and the historical processing data of each base station within its own area one by one; finally, the arbitration base station selects the base station within its own area with the highest similarity and the similarity exceeding the predetermined threshold as the corresponding alternative base station.

[0146] Furthermore, if no base station with a similarity exceeding the threshold is found, it is considered that there is no suitable alternative base station for the competing base station within its own area. A direct vote is conducted on the competing base station.

[0147] A2.2: Sort all the base stations within the self-arbitration area in descending order of idle load to obtain an idle load sequence;

[0148] In this embodiment, the arbitration base station needs to reasonably arrange service allocation according to the resource usage status of the base stations within the area. Therefore, the arbitration base station first regularly collects and statistically analyzes the idle load information of each base station within the area through the edge computing nodes configured by itself.

[0149] Specifically, it monitors in real time the utilization rate of physical resource blocks (PRBs), the number of user connections, throughput data, and the utilization rate of the CPU or baseband unit, and calculates the real-time idle load index of each base station based on this comprehensive information, indicating the capacity of the remaining resources of the base station. The arbitration base station then sorts the idle load indexes of all base stations to obtain a complete idle load sequence. The base station with a larger load index is the base station with a higher degree of resource idleness and a larger remaining capacity. When it is necessary to evaluate the necessity of competing base stations outside the area to participate in the competition, it is possible to clearly and intuitively understand the remaining resources of the base stations within the area, which helps to accurately judge the actual service carrying value of the competing base stations in the subsequent steps and avoid waste or resource shortage problems caused by unreasonable resource allocation.

[0150] A2.3: For each competing base station with an alternative base station, determine the sequence position of the corresponding alternative base station. If the sequence position of the corresponding alternative base station is after the set position, confirm to vote for the competing base station;

[0151] Specifically, the arbitration base station first defines a preset threshold position of the load sequence, which is used as a threshold benchmark for indicating the resource tension degree in the area. For example, if the threshold position is set to the median position of the sequence, the base stations after this position represent the base stations with relatively tight resources or relatively high load; if the alternative base station is located after the set threshold position, it means that the base station resources in the arbitration area are relatively busy. At this time, if the competing base station can be selected as the serving base station, it can effectively relieve the service pressure in this area. Therefore, the arbitration base station confirms to vote for the corresponding competing base station outside the area. On the contrary, if the alternative base station is located before the threshold position, that is, the resources are relatively abundant, it indicates that there are already sufficient resources in the current area to handle the service requirements, and there is no need to introduce additional competing base stations outside the area to participate in service bearing. Therefore, the vote for this competing base station is abandoned. This judgment strategy based on the load sorting position of the alternative base station can intuitively reflect the resource tension degree in the current area and the actual necessity of the competing base station to participate in the service, avoid the defects of making decisions simply based on static competition indicators, and effectively improve the accuracy of the voting decision and the optimization utilization efficiency of network resources.

[0152] A2.4: Receive the voting votes of each competing base station sent by other arbitration base stations, connect with the voting votes of each competing node determined by itself, and summarize to determine the serving base station;

[0153] Specifically, the arbitration base station first encodes its voting results for each competing base station, including the identifier of the competing base station supported by the vote, and broadcasts its voting information to the entire distributed base station cluster through a predefined distributed communication protocol, such as the X2 interface or other dedicated signaling channels. Then, the arbitration base station receives and parses the voting information from other arbitration base stations, and performs real-time summarization of the voting data through the edge computing node to form the vote count result for each competing base station. The arbitration base station ensures the consistency and accuracy of the voting results through real-time data synchronization. If multiple competing base stations obtain the same number of votes during the summarization process, the arbitration base station further executes multi-level preference rules in sequence according to information such as the service load index, channel quality level, base station energy consumption index, historical user connection success rate, and response delay provided by the competing base stations, and finally determines the only serving base station. Make full use of the information sharing and collaborative decision-making capabilities of each base station in the entire distributed arbitration mechanism, avoid inaccurate results caused by the judgment deviation of a single base station, improve the accuracy, reliability, and objectivity of the serving base station selection, so as to allocate network resources more reasonably, ensure efficient service bearing while achieving significant energy-saving effects.

[0154] The specific steps of A2.4 are as follows:

[0155] A2.4.1: Each arbitration base station generates voting information according to its determined voting results, and the voting information includes the identifiers of the competing base stations that obtain the vote of this arbitration base station;

[0156] A2.4.2: Broadcast its own voting information to the distributed base station cluster;

[0157] A2.4.3: Receive the voting information broadcast by other arbitration base stations, and combine its own voting information to count the number of votes obtained by each competing base station;

[0158] A2.4.4: Select the competing base station with the most votes as the serving base station;

[0159] When multiple competing base stations obtain the same maximum number of votes, A2.4 further includes:

[0160] A2.4.5: Obtain the traffic load index, channel quality level, and base station energy consumption index in the competition information;

[0161] A2.4.6: Compare the traffic load indices of competing base stations with the same number of votes, and select the base station with the highest traffic load index as the serving base station;

[0162] A2.4.7: If the traffic load indices are the same, then compare the channel quality levels and select the base station with the highest channel quality level as the serving base station;

[0163] A2.4.8: If the channel quality levels are the same, then compare the base station energy consumption indices and select the base station with the lowest base station energy consumption index as the serving base station;

[0164] A2.4.9: If the base station energy consumption indices are the same, then select the base station with the highest historical user connection success rate as the serving base station;

[0165] A2.4.10: If the historical user connection success rates are the same, then select the base station with the shortest response delay from the last wake-up from the dormant state to the active state as the serving base station.

[0166] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. An energy-saving method for intelligent sleep and wake-up of 5G base stations based on edge computing, which is applied to competing base stations in a distributed base station cluster. The distributed base station cluster further includes a plurality of arbitration base stations. Each arbitration base station is one of the base stations in the distributed base station cluster that are not currently participating in the competition. Each arbitration base station corresponds to an arbitration area composed of a plurality of base stations. Each base station is configured with an edge computing node, and is characterized in that, The intelligent sleep and wake-up energy-saving method for 5G base stations includes: Receiving the network response requests of user terminals broadcast by the distributed base station cluster; Generating competition information according to competition metrics, and broadcasting the competition information and historical processing information to the distributed base station cluster, so that each arbitration base station votes for a serving base station based on the received competition information and historical processing information of competing base stations; If the competing base station is selected as the serving base station, switch its own state to or maintain the wake-up state; The competition metrics include service load, channel quality, and base station energy consumption. Generating competition information according to the competition metrics includes: Obtaining the current service load, where the current service load includes PRB occupancy rate, number of user connections, and throughput, and calculating the service load index according to a preset weight; Obtaining channel quality metrics, where the channel quality metrics include RSRP, SINR, and path loss, and calculating the channel quality level according to the channel quality threshold; Obtaining the current power consumption, energy efficiency per bit, and switching energy consumption overhead, and calculating the base station energy consumption index; Judging whether to compete for the network response request according to the service load index, channel quality level, and base station energy consumption index. If so, construct competition information. If not, broadcast the base station identification information to the distributed base station cluster to serve as an arbitration base station; The historical processing information includes historical user connection success rate, historical average throughput, and historical channel quality fluctuation; 2. The intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing according to claim 1, characterized in that, Judging whether to compete for the network response request according to the service load index, channel quality level, and base station energy consumption index includes: Comparing the service load index with a first threshold to judge whether the current base station service load is higher than the first threshold, where the first threshold is adjusted by the edge computing node according to historical load data; If the service load index is higher than the first threshold, it is determined that the response request needs to be competed for; If the service load index is less than or equal to the first threshold, further compare the channel quality level with a second threshold. When the channel quality level is greater than or equal to the second threshold, further compare the base station energy consumption index with a third threshold, otherwise give up competing, where the second threshold is determined by all arbitration base stations in the previous round based on the average received signal quality reported by the user terminal; If the base station energy consumption index is less than the third threshold, it is determined that the response request needs to be competed for; otherwise, give up competing.

3. The 5G base station intelligent sleep and wake-up energy-saving method based on edge computing is applied to the arbitration base stations in a distributed base station cluster. Each arbitration base station corresponds to an arbitration area composed of multiple base stations. The distributed base station cluster also includes multiple competing base stations. Each arbitration base station is one of the base stations that are not currently participating in the competition in the distributed base station cluster. Each base station is configured with an edge computing node, and is characterized in that, The intelligent sleep and wake-up energy-saving method for 5G base stations includes: Receiving the competition information and historical processing information sent by each competing base station not in its own arbitration area; Voting for a serving base station according to the competition information and historical processing information corresponding to each competing base station; Broadcasting the base station identification of the serving base station to the distributed base station cluster, so that the corresponding competing base station switches its own state to or maintains the wake-up state; Among them, the competition information is generated by competition metrics. The competition metrics include service load, channel quality, and base station energy consumption. Generating the competition information by competition metrics includes: Obtain the current service load, where the current service load includes PRB occupancy rate, number of user connections, and throughput, and calculate the service load index according to preset weights; Obtain the channel quality indicators, where the channel quality indicators include RSRP, SINR, and path loss, and calculate the channel quality level according to the channel quality threshold; Obtain the current power consumption, energy efficiency per bit, and switching energy consumption overhead, and calculate the base station energy consumption index; Judge whether a competitive network response request is needed according to the service load index, channel quality level, and base station energy consumption index. If so, construct competitive information. If not, broadcast the base station identification information to the distributed base station cluster to serve as an arbitration base station; The historical processing information includes historical user connection success rate, historical average throughput, and historical channel quality fluctuation; 4. The intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing according to claim 3, wherein, Voting for a serving base station according to the competitive information and historical processing information corresponding to each competitive base station includes: For each competitive base station, determine whether there is a corresponding alternative base station in its own arbitration area according to the competitive information and historical processing information corresponding to each competitive base station; Sort all the base stations in the own arbitration area in descending order of idle load to obtain an idle load sequence; For each competitive base station with an alternative base station, determine the sequence position of the corresponding alternative base station. If the sequence position of the corresponding alternative base station is after the set position, confirm to vote for this competitive base station; Receive the voting votes of each competitive base station sent by other arbitration base stations, connect the voting votes of each competitive node determined by itself, and summarize to determine the serving base station; 5. The intelligent sleep and wake-up energy-saving method for a 5G base station based on edge computing according to claim 4, wherein, Determining whether there is a corresponding alternative base station in the own arbitration area includes: According to the historical processing information of the competitive base station, calculate the similarity between the historical processing information of this competitive base station and that of each base station in its own arbitration area; According to the similarity, select the base station with the highest similarity to the historical processing information of each competitive base station in its own arbitration area as the corresponding alternative base station; 6. The intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing according to claim 4, wherein Summarizing and determining the serving base station includes: Each arbitration base station generates voting information according to its own determined voting result. The voting information includes the identifiers of each competitive base station that obtains the vote of this arbitration base station; Broadcast its own voting information to the distributed base station cluster; Receive the voting information broadcast by other arbitration base stations, and combine with its own voting information to count the voting votes obtained by each competitive base station; Take the competitive base station with the most voting votes as the serving base station; 7. The intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing according to claim 6, wherein, When multiple competitive base stations obtain the same highest voting votes, the summarizing and determining the serving base station further includes: Obtain the service load index, channel quality level, and base station energy consumption index in the competitive information; Sequentially execute the preference rules until a unique serving base station is determined; 8. The intelligent sleep and wake-up energy-saving method for a 5G base station based on edge computing according to claim 7, wherein Sequentially executing the preference rules until a unique serving base station is determined includes: Compare the service load indexes of the competitive base stations with the same voting votes, and select the base station with the highest service load index as the serving base station; If the service load indexes are the same, then compare the channel quality levels, and select the base station with the highest channel quality level as the serving base station; If the channel quality levels are the same, compare the base station energy consumption indexes, and select the base station with the lowest base station energy consumption index as the serving base station; If the base station energy consumption indexes are the same, select the base station with the highest historical user connection success rate as the serving base station; If the historical user connection success rates are the same, select the base station with the shortest response delay from the most recent wake-up from the dormant state to the active state as the serving base station.

9. The intelligent sleep and wake-up energy-saving method for 5G base stations based on edge computing according to claim 3, wherein When the number of arbitration base stations does not meet the preset base threshold, the 5G base station intelligent sleep and wake-up energy saving method further includes: According to the competition information of each competing base station, perform reverse sorting on the competition information to generate a reverse list; Sequentially convert the competing base stations in the reverse list into arbitration base stations one by one until the number of arbitration base stations meets the preset base threshold.

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