Wireless network energy efficiency assessment method and device, and storage medium

Abstract

The invention provides a wireless network energy efficiency evaluation method and device and a storage medium, and is applied to the field of communication. The method comprises the following steps: acquiring network performance data of a base station, energy consumption data of equipment and a service type corresponding to a wireless network service; determining a corresponding quality factor based on the service type, determining service output based on the performance data, and determining effective energy consumption of the equipment based on the energy consumption data; and determining the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption. According to the method, the technical effect of improving the accuracy of energy efficiency evaluation is achieved.

Description

Technical Field

[0001] The present application relates to the field of communications, and in particular to a method, device and storage medium for evaluating energy efficiency of a wireless network. Background Art

[0002] With the popularization of wireless networks and the increase in energy consumption of network equipment, society has become concerned about energy consumption issues. The evaluation of wireless network energy efficiency has become an important direction for the development of Internet technology.

[0003] The 3GPP protocol defines three types of services for 5G networks: eMBB, uRLLC, and mMTC. In the eMBB service type, the energy efficiency level of the eMBB service type is evaluated by detecting the amount of data transmitted and the spectrum resources used; in the uRLLC service type, the energy efficiency level of the uRLLC service type is evaluated by detecting the energy consumption and the amount of data transmitted; in the mMTC service type, the energy efficiency level of the mMTC service type is evaluated by detecting the number of devices supported and the unit area.

[0004] In the existing energy efficiency calculation, for eMBB business type services, the energy efficiency calculation mainly considers the business volume dimension, does not consider the goal of wireless network construction, ignores the output effect of base stations built for the purpose of coverage, and performs energy efficiency calculation based on business volume, which weakens the actual effective output of coverage base stations; the existing energy efficiency calculation is to add the calculation of effective energy consumption of renewable resources, which reduces the accuracy of wireless network energy efficiency calculation; in the energy efficiency calculation for different business types, the overall energy efficiency evaluation is conducted in conjunction with multiple business scenarios and multiple construction goals, and the evaluation method is single and lacks systematicity; therefore, in the existing energy efficiency evaluation, there is a technical problem of low accuracy of energy efficiency evaluation. Summary of the invention

[0005] The present application provides a wireless network energy efficiency evaluation method, device and storage medium to solve the technical problem of low accuracy of energy efficiency evaluation in existing energy efficiency evaluation.

[0006] In a first aspect, the present application provides a wireless network energy efficiency evaluation method, comprising:

[0007] Obtain network performance data of base stations, energy consumption data of equipment, and service types corresponding to wireless network services;

[0008] Determine the corresponding quality factor based on the service type, determine the service output based on the performance data, and determine the effective energy consumption of the equipment based on the energy consumption data;

[0009] The target energy efficiency corresponding to the service type is determined based on the ratio of the product of the quality factor and the service output to the effective energy consumption.

[0010] Optionally, determining a corresponding quality factor based on a service type, determining a service output based on performance data, and determining effective energy consumption of a device based on energy consumption data include:

[0011] Determine whether the service type is an eMBB service type, and if so, determine the corresponding main scenario type and quality factor based on the wireless network service;

[0012] Determine the service output based on the main scenario type, quality factors and performance data;

[0013] The preset renewable energy usage time ratio of the device is determined based on the energy consumption data, and the first effective energy consumption of the device is determined based on the preset renewable energy usage time ratio.

[0014] Optionally, determining a corresponding main scenario type and a quality factor based on a wireless network service includes:

[0015] When the main scenario type is determined to be capacity type based on the wireless network service, a corresponding first quality factor is determined based on an RLC layer uplink retransmission rate and an RLC layer downlink retransmission rate corresponding to the eMBB service type;

[0016] When the main scenario type is determined to be coverage type based on the wireless network service, a coverage quality factor acquisition method of the eMBB service type is obtained, and a second quality factor corresponding to the coverage type is determined based on the acquisition method.

[0017] Optionally, determining the service output based on the main scenario type, the quality factor, and the performance data includes:

[0018] Determine based on the performance data that when the eMBB service type is a capacity type in the primary scenario, determine the service volume of the RLC layer, and determine the first service output based on the service volume;

[0019] Based on the performance data, when the eMBB service type is a coverage type in the main scenario, the base station signal coverage area corresponding to the coverage type is determined, and the second service output is determined based on the base station signal coverage area.

[0020] Optionally, determining a corresponding quality factor based on a service type, determining a service output based on performance data, and determining effective energy consumption of a device based on energy consumption data further includes:

[0021] When the service type is a uRLLC service type, determining a third quality factor corresponding to the uRLLC service type;

[0022] Determine the network reliability and end-to-end delay corresponding to the uRLLC service type based on the performance data, and determine the third service output corresponding to the uRLLC service type;

[0023] The network slicing method based on the uRLLC service type determines the slice energy consumption corresponding to the uRLLC service type, and determines the corresponding second effective energy consumption based on the slice energy consumption.

[0024] Optionally, determining a corresponding quality factor based on a service type and determining a service output based on performance data further includes:

[0025] When the service type is an mMTC service type, determining a third quality factor corresponding to the mMTC service type;

[0026] Determine the number of supported connections corresponding to the mMTC service type based on the performance data, and determine a fourth service output corresponding to the mMTC service type;

[0027] The network slicing method based on the mMTC service type determines the slice energy consumption corresponding to the mMTC service type, and determines the corresponding third effective energy consumption based on the slice energy consumption.

[0028] Optionally, determining the energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption includes:

[0029] When the service type is an eMBB service type, determining a first energy efficiency based on a ratio of a product of a first quality factor and a first service output to a first effective energy consumption;

[0030] Determining a second energy efficiency based on a ratio of a product of a second quality factor and a second service output to the first effective energy consumption;

[0031] Determine a target energy efficiency corresponding to the eMBB service type based on the first energy efficiency and the second energy efficiency;

[0032] When the service type is a uRLLC service type, a ratio of a product of the third quality factor and the third service output to the second effective energy consumption is determined as a third energy efficiency, and the third energy efficiency is determined as a target energy efficiency corresponding to the uRLLC service type;

[0033] When the service type is the mMTC service type, the ratio of the product of the third quality factor and the fourth service output to the third effective energy consumption is determined as the fourth energy efficiency, and the fourth energy efficiency is determined as the target energy efficiency corresponding to the mMTC service type.

[0034] Optionally, after determining the target energy efficiency corresponding to the eMBB service type based on the first energy efficiency and the second energy efficiency, the method further includes any one of the following items:

[0035] Comparing an average value of the first energy efficiency and an average value of the second energy efficiency of the eMBB service type in different wireless networks, and obtaining a comparison result;

[0036] Determine an average value of two first energy efficiencies corresponding to the eMBB service type based on any two wireless networks, calculate a comparison coefficient based on the distribution of uplink traffic and downlink traffic of base stations corresponding to the two wireless networks, and compare and calculate the average values ​​of the two first energy efficiencies based on the comparison coefficient, and determine a comparison result;

[0037] The unit energy efficiency of the average value of the first energy efficiency and the unit energy efficiency of the average value of the second energy efficiency of the eMBB service type in the same wireless network are compared based on the preset weight, and a comparison result is obtained.

[0038] Optionally, after determining the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption, the method further includes:

[0039] Determine the planned business output, planned quality factor and planned effective energy consumption based on the preset planning data, and calculate the predicted energy efficiency corresponding to the planned business output, planned quality factor and planned effective energy consumption based on the preset energy efficiency formula;

[0040] Perform fitting calculation based on preset planning data and predicted energy efficiency, and determine the fitting curve;

[0041] The predicted business output is predicted and determined based on the fitting curve, and the predicted energy consumption is calculated and determined based on the predicted business output.

[0042] In a second aspect, the present application provides a wireless network energy efficiency evaluation device, including:

[0043] An acquisition module is used to obtain network performance data of base stations, energy consumption data of devices, and service types corresponding to wireless network services;

[0044] A processing module, used to determine a corresponding quality factor based on a service type, determine a service output based on performance data, and determine an effective energy consumption of a device based on energy consumption data;

[0045] The determination module is used to determine the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption.

[0046] Optionally, the device is also used to:

[0047] Determine whether the service type is an eMBB service type, and if so, determine the corresponding main scenario type and quality factor based on the wireless network service;

[0048] Determine the service output based on the main scenario type, quality factors and performance data;

[0049] The preset renewable energy usage time ratio of the device is determined based on the energy consumption data, and the first effective energy consumption of the device is determined based on the preset renewable energy usage time ratio.

[0050] Optionally, the device is also used to:

[0051] When the main scenario type is determined to be capacity type based on the wireless network service, a corresponding first quality factor is determined based on an RLC layer uplink retransmission rate and an RLC layer downlink retransmission rate corresponding to the eMBB service type;

[0052] When the main scenario type is determined to be coverage type based on the wireless network service, a coverage quality factor acquisition method of the eMBB service type is obtained, and a second quality factor corresponding to the coverage type is determined based on the acquisition method.

[0053] Optionally, the device is also used to:

[0054] Determine based on the performance data that when the eMBB service type is a capacity type in the primary scenario, determine the service volume of the RLC layer, and determine the first service output based on the service volume;

[0055] Based on the performance data, when the eMBB service type is a coverage type in the main scenario, the base station signal coverage area corresponding to the coverage type is determined, and the second service output is determined based on the base station signal coverage area.

[0056] Optionally, the device is also used to:

[0057] When the service type is a uRLLC service type, determining a third quality factor corresponding to the uRLLC service type;

[0058] Determine the network reliability and end-to-end delay corresponding to the uRLLC service type based on the performance data, and determine the third service output corresponding to the uRLLC service type;

[0059] The network slicing method based on the uRLLC service type determines the slice energy consumption corresponding to the uRLLC service type, and determines the corresponding second effective energy consumption based on the slice energy consumption.

[0060] Optionally, the device is also used to:

[0061] When the service type is an mMTC service type, determining a third quality factor corresponding to the mMTC service type;

[0062] Determine the number of supported connections corresponding to the mMTC service type based on the performance data, and determine a fourth service output corresponding to the mMTC service type;

[0063] The network slicing method based on the mMTC service type determines the slice energy consumption corresponding to the mMTC service type, and determines the corresponding third effective energy consumption based on the slice energy consumption.

[0064] Optionally, the device is also used to:

[0065] When the service type is an eMBB service type, determining a first energy efficiency based on a ratio of a product of a first quality factor and a first service output to a first effective energy consumption;

[0066] Determining a second energy efficiency based on a ratio of a product of a second quality factor and a second service output to the first effective energy consumption;

[0067] Determine a target energy efficiency corresponding to the eMBB service type based on the first energy efficiency and the second energy efficiency;

[0068] When the service type is a uRLLC service type, a ratio of a product of the third quality factor and the third service output to the second effective energy consumption is determined as a third energy efficiency, and the third energy efficiency is determined as a target energy efficiency corresponding to the uRLLC service type;

[0069] When the service type is the mMTC service type, the ratio of the product of the third quality factor and the fourth service output to the third effective energy consumption is determined as the fourth energy efficiency, and the fourth energy efficiency is determined as the target energy efficiency corresponding to the mMTC service type.

[0070] Optionally, the device is also used to:

[0071] Comparing an average value of the first energy efficiency and an average value of the second energy efficiency of the eMBB service type in different wireless networks, and obtaining a comparison result;

[0072] Determine an average value of two first energy efficiencies corresponding to the eMBB service type based on any two wireless networks, calculate a comparison coefficient based on the distribution of uplink traffic and downlink traffic of base stations corresponding to the two wireless networks, and compare and calculate the average values ​​of the two first energy efficiencies based on the comparison coefficient, and determine a comparison result;

[0073] The unit energy efficiency of the average value of the first energy efficiency and the unit energy efficiency of the average value of the second energy efficiency of the eMBB service type in the same wireless network are compared based on the preset weight, and a comparison result is obtained.

[0074] Optionally, the device is also used to:

[0075] Determine the planned business output, planned quality factor and planned effective energy consumption based on the preset planning data, and calculate the predicted energy efficiency corresponding to the planned business output, planned quality factor and planned effective energy consumption based on the preset energy efficiency formula;

[0076] Perform fitting calculation based on preset planning data and predicted energy efficiency, and determine the fitting curve;

[0077] The predicted business output is predicted and determined based on the fitting curve, and the predicted energy consumption is calculated and determined based on the predicted business output.

[0078] In a third aspect of the present application, a wireless network energy efficiency evaluation device is provided, comprising:

[0079] Processor and memory;

[0080] Memory stores computer-executable instructions;

[0081] The processor executes the computer-executable instructions stored in the memory, so that the wireless network energy efficiency evaluation device executes any one of the wireless network energy efficiency evaluation methods in the first aspect.

[0082] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement a wireless network energy efficiency evaluation method as described in any one of the first aspects.

[0083] The present application provides a wireless network energy efficiency evaluation method, device and storage medium. The method includes: obtaining network performance data of base stations, energy consumption data of devices, and service types corresponding to wireless network services; determining the corresponding quality factor based on the service type, determining the service output based on the performance data, and determining the effective energy consumption of the device based on the energy consumption data; determining the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption. Based on the acquired network performance data and equipment energy consumption data, the service output, quality factor and effective energy consumption corresponding to the wireless network are determined; according to different service types of the wireless network, the quality factor, service output and effective energy consumption of energy efficiency calculation corresponding to different service types are determined, and the target energy efficiency corresponding to different service types is calculated and obtained; and the energy efficiency evaluation of the wireless network is realized based on the target energy efficiency; compared with the prior art, the present application considers the impact of renewable energy in the calculation of effective energy consumption, considers the energy efficiency under different main scenarios in the eMBB service type, and comprehensively evaluates the overall wireless network energy efficiency, obtains the slice energy consumption of the wireless network for the uRLLC service type and the mM TC service type, determines the quality factor and service output based on the actual measurement value, and calculates the corresponding slice energy efficiency to realize the evaluation of the wireless network energy efficiency; by calculating the wireless network energy efficiency for different types of service outputs and different service types, the accuracy of the energy efficiency evaluation is increased; thereby achieving the technical effect of improving the accuracy of the energy efficiency evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0085] Figure 1 The process of the wireless network energy efficiency evaluation method provided in the embodiment of the present application Figure 1 ;

[0086] Figure 2 The process of the wireless network energy efficiency evaluation method provided in the embodiment of the present application Figure 2 ;

[0087] Figure 3 The process of the wireless network energy efficiency evaluation method provided in the embodiment of the present application Figure 3 ;

[0088] Figure 4 A flowchart of an energy consumption prediction method based on wireless network energy efficiency evaluation provided in an embodiment of the present application;

[0089] Figure 5 A schematic diagram of the structure of a wireless network energy efficiency evaluation device provided in an embodiment of the present application;

[0090] Figure 6 A hardware structure diagram of the wireless network energy efficiency evaluation device provided in an embodiment of the present application.

[0091] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0092] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0093] First, the terms involved in this application are explained:

[0094] Enhanced Mobile Broadband (eMBB service type): It is an application scenario in 5G networks, mainly for mobile broadband users, providing higher data transmission rates and lower latency to meet the needs of high-traffic applications such as high-definition video, virtual reality, and augmented reality.

[0095] Ultra-Reliable and Low Latency Communications (uRLLC): is an application scenario in 5G networks, mainly for applications with extremely high requirements for communication delay and reliability, such as autonomous driving, telemedicine, and industrial automation. uRLLC requires the network to have extremely low transmission delay and extremely high reliability to ensure real-time and reliability.

[0096] Massive Machine Type Communications (mMTC): It is an application scenario in 5G networks, mainly for IoT applications such as smart homes, smart cities, and smart transportation. mMTC requires the network to support large-scale device connections and data transmission to meet the communication needs of massive devices in the IoT.

[0097] Radio Resource Control (RRC): refers to the management, control and scheduling of radio resources through certain strategies and means, making full use of limited wireless network resources while meeting the requirements of service quality, ensuring that the planned coverage area is reached, and improving service capacity and resource utilization.

[0098] Radio Access Technology (RAT): The basic physical link method applicable to wireless communication networks. Multiple radio access technologies can be supported in one device.

[0099] Radio Link Control (RLC): Part of the data plane protocol in the wireless protocol architecture, used for but not limited to data segmentation and reassembly, connection control, and flow control.

[0100] New Radio (NR): refers to the 5G wireless network, which aims to provide higher data transmission rates, lower and better network capacity to meet future needs for mobile communications.

[0101] 3GPP Long Term Evolution (LTE): It is the current mainstream mobile communication technology, providing higher speed and lower latency.

[0102] The 3GPP protocol defines three types of services for 5G networks: eMBB, uRLLC, and mMTC. In the eMBB service type, the energy efficiency level of the eMBB service type is evaluated by detecting the amount of data transmitted and the spectrum resources used; in the uRLLC service type, the energy efficiency level of the uRLLC service type is evaluated by detecting the energy consumption and the amount of data transmitted; in the mMTC service type, the energy efficiency level of the mMTC service type is evaluated by detecting the number of devices supported and the unit area. In the existing energy efficiency calculation, for eMBB business type services, the energy efficiency calculation mainly considers the business volume dimension, does not consider the goal of wireless network construction, ignores the output effect of base stations built for the purpose of coverage, and performs energy efficiency calculation based on business volume, which weakens the actual effective output of coverage base stations; the existing energy efficiency calculation is to add the calculation of effective energy consumption of renewable resources, which reduces the accuracy of wireless network energy efficiency calculation; in the energy efficiency calculation for different business types, the overall energy efficiency evaluation is conducted in conjunction with multiple business scenarios and multiple construction goals, and the evaluation method is single and lacks systematicity; therefore, in the existing energy efficiency evaluation, there is a technical problem of low accuracy of energy efficiency evaluation.

[0103] The present application provides a wireless network energy efficiency evaluation method, device and storage medium. The method includes: obtaining network performance data of base stations, energy consumption data of devices, and service types corresponding to wireless network services; determining the corresponding quality factor based on the service type, determining the service output based on the performance data, and determining the effective energy consumption of the device based on the energy consumption data; determining the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption. Based on the acquired network performance data and equipment energy consumption data, the service output, quality factor and effective energy consumption corresponding to the wireless network are determined; according to different service types of the wireless network, the quality factor, service output and effective energy consumption of energy efficiency calculation corresponding to different service types are determined, and the target energy efficiency corresponding to different service types is calculated and obtained; and the energy efficiency evaluation of the wireless network is realized based on the target energy efficiency; compared with the prior art, the present application considers the impact of renewable energy in the calculation of effective energy consumption, considers the energy efficiency under different main scenarios in the eMBB service type, and comprehensively evaluates the overall wireless network energy efficiency, obtains the slice energy consumption of the wireless network for the uRLLC service type and the mM TC service type, determines the quality factor and service output based on the actual measurement value, and calculates the corresponding slice energy efficiency to realize the evaluation of the wireless network energy efficiency; by calculating the energy efficiency of the wireless network for different types of service outputs and different service types, the accuracy of the energy efficiency evaluation is increased; thereby achieving the technical effect of improving the accuracy of the energy efficiency evaluation, and solving the technical problem of low accuracy of the energy efficiency evaluation in the prior art.

[0104] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0105] Figure 1 The process of the wireless network energy efficiency evaluation method provided in the embodiment of the present application Figure 1 .like Figure 1 As shown, the wireless network energy efficiency evaluation method provided by the embodiment of the present application includes:

[0106] S101, obtaining network performance data of the base station, energy consumption data of the device, and service types corresponding to the wireless network service;

[0107] In this embodiment, in this embodiment, the service types corresponding to the wireless network include: eMBB service type, uRLLC service type and mMTC service type; in this embodiment, the network performance data of the base station is obtained through the device network management of the wireless network, and the device uploads the energy consumption data to the device network management; wherein, the network performance data of the base station is various performance indicator data generated by the base station during operation, including the service volume, latency and number of RRC connections of the base station; the energy consumption data of the device refers to the energy consumed by the device when using the wireless network, which may include data such as the power consumption, energy life and charging time of the device. The energy consumption of the device needs to distinguish different wireless access technologies. For multi-mode sites, the energy consumption of the device should be allocated proportionally between each RAT according to the configured radio frequency power transmitted by each RAT.

[0108] S102, determining a corresponding quality factor based on the service type, determining a service output based on the performance data, and determining an effective energy consumption of the device based on the energy consumption data;

[0109] In this embodiment, the service output of the base station includes but is not limited to: data communication, SMS service output, multimedia communication output, and location service output; the effective energy consumption of the device refers to the energy consumed by the device when completing a specific task or providing a specific function.

[0110] S103: Determine a target energy efficiency corresponding to the service type based on a ratio of a product of the quality factor and the service output to the effective energy consumption.

[0111] In this embodiment, the calculation formula of energy efficiency is: EE=(TO*QF) / EC; wherein EE is energy efficiency, TO is traffic output, QF is quality factor, and EC is effective energy consumption of the device; according to the definition of 5G network, the product of traffic output and quality factor is the effective output of the network.

[0112] The present application provides a method for evaluating the energy efficiency of a wireless network. The method includes: obtaining network performance data of a base station, energy consumption data of a device, and a service type corresponding to a wireless network service; determining a corresponding quality factor based on the service type, determining service output based on performance data, and determining effective energy consumption of the device based on energy consumption data; and determining a target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and service output to the effective energy consumption. Based on the acquired network performance data and equipment energy consumption data, the service output, quality factor and effective energy consumption corresponding to the wireless network are determined; according to different service types of the wireless network, the quality factor, service output and effective energy consumption of the energy efficiency calculation corresponding to different service types are determined, and the target energy efficiency corresponding to different service types is calculated and obtained; and the energy efficiency evaluation of the wireless network is realized based on the target energy efficiency; compared with the prior art, the present application considers the impact of renewable energy in the calculation of effective energy consumption, considers the energy efficiency under different main scenarios in the eMBB service type, and comprehensively evaluates the overall wireless network energy efficiency, obtains the slice energy consumption of the wireless network for the uRLLC service type and the mMTC service type, determines the quality factor and service output based on the actual measurement value, and calculates the corresponding slice energy efficiency to realize the evaluation of the wireless network energy efficiency; by calculating the energy efficiency of the wireless network for different types of service outputs and different service types, the accuracy of the energy efficiency evaluation is increased; thereby achieving the technical effect of improving the accuracy of the energy efficiency evaluation, and solving the technical problem of low accuracy of the energy efficiency evaluation in the prior art.

[0113] Figure 2 The process of the wireless network energy efficiency evaluation method provided in the embodiment of the present application Figure 2 , Figure 3 The process of the wireless network energy efficiency evaluation method provided in the embodiment of the present application Figure 3 , Figure 4 The flowchart of the energy consumption prediction method based on wireless network energy efficiency evaluation provided in the embodiment of the present application is as follows. Figure 2 , Figure 3 and Figure 4 As shown, the wireless network energy efficiency evaluation method provided by the embodiment of the present application includes:

[0114] S201, obtaining network performance data of the base station, energy consumption data of the device, and service types corresponding to the wireless network service;

[0115] S202, determining whether the service type is an eMBB service type, and if so, when the main scenario type is determined to be a capacity type based on the wireless network service, determining a corresponding first quality factor based on an RLC layer uplink retransmission rate and an RLC layer downlink retransmission rate corresponding to the eMBB service type; when the main scenario type is determined to be a coverage type based on the wireless network service, obtaining a coverage quality factor acquisition method of the eMBB service type, and determining a second quality factor corresponding to the coverage type based on the acquisition method;

[0116] In this embodiment, the eMBB service type is applied to the wide area network, the uRLLC service type and the mMTC service type are applied to the local area private network or the sliced ​​network. The uplink retransmission rate of the RLC layer and the downlink retransmission rate of the RLC layer are: when an error or loss occurs in the data sent by the base station during the transmission process, the RLC layer will trigger the retransmission mechanism and resend the data to ensure the reliable transmission of the data; wherein the uplink retransmission rate refers to the proportion of retransmissions occurring during the uplink data transmission process, and the uplink data refers to the data sent from the terminal device to the base station; the downlink retransmission rate refers to the proportion of retransmissions occurring during the downlink data transmission process of the RLC layer in wireless communication, and the downlink data refers to the data sent from the base station to the terminal device.

[0117] like Figure 3 As shown, in the first example, the traffic quality factor is 1-the uplink retransmission rate or the downlink retransmission rate of the RLC layer, that is, the first quality factor.

[0118] In this embodiment, when the main scenario type is coverage type, the method for obtaining the coverage quality factor of the eMBB service type can be: collecting data according to indicators or performing traversal tests; the traversal tests include: call quality test (Coverage Quality Test, CQT) and drive test (Drive Test, DT).

[0119] like Figure 3 As shown, in the second example, the coverage quality factor is obtained through the CQT / DT traversal test, and the coverage quality factor reference signal received power (Reference Signal Received Power, RSRP) is greater than the proportion of the preset threshold. In this example, the preset threshold is set to 105dB, and the proportion exceeding 105dB is the coverage quality factor, that is, the second quality factor.

[0120] In the third exemplary embodiment, the coverage quality factor is determined by the indicator collection data, and the coverage quality factor is equal to the product of the access coverage quality factor and the connection coverage factor; wherein the access coverage factor is the RRC connection establishment success rate of the access process, and the connection coverage factor is the handover and redirection ratio caused by coverage in the connected state;

[0121] The calculation of the connection coverage factor is:

[0122]

[0123] Among them, the number of NR switching LTE requests and the total number of 5G redirection to 4G are triggered by data coverage.

[0124]

[0125] Among them, the final connection coverage factor is obtained by subtracting the ratio of 1 to the number of NR switching LTE requests triggered by data reasons and the total number of 5G redirections to 4G and the number of NR switching LTE requests triggered by data coverage and the total number of 5G redirections to 4G, thereby determining the coverage quality factor and obtaining the second quality factor.

[0126] Among them, the number of successful NR to LTE switching refers to the number of successful switching when switching between NR and LTE; this indicator measures the effect and performance of switching between 5G and LTE; the total number of 5G redirections to 4G refers to the total number of times the user device is forced to switch to the 4G network in the 5G network due to some reasons, including but not limited to: weak signal, network congestion. This indicator is used to measure the stability of the 5G network. The signal requires the device to switch to the 4G network. The total number of redirections to 4G can reflect the coverage, signal quality and network load of the 5G network. The total number of data coverage triggers 5G interoperability to 4G refers to the number of times the user device automatically switches to the 4G network for data transmission in areas not covered by the 5G network.

[0127] S203, determining the service volume of the RLC layer when the main scenario is the capacity type based on the performance data, and determining the first service output based on the service volume; determining the base station signal coverage area corresponding to the coverage type when the main scenario is the coverage type based on the performance data, and determining the second service output based on the base station signal coverage area; determining the preset renewable energy usage time ratio of the device based on the energy consumption data, and determining the first effective energy consumption of the device based on the preset renewable energy usage time ratio;

[0128] In this embodiment, when the main scenario is capacity type, the uplink service volume and downlink service volume of the RLC layer are obtained as the first service output; when the main scenario is coverage type, the area within a certain signal coverage range of the base station is used as the second service output; the first effective energy consumption is obtained by subtracting the proportion of renewable energy from the energy consumption of the equipment.

[0129] S204. When the service type is an eMBB service type, determine a first energy efficiency based on a ratio of a product of a first quality factor and a first service output to a first effective energy consumption; determine a second energy efficiency based on a ratio of a product of a second quality factor and a second service output to the first effective energy consumption; and determine a target energy efficiency corresponding to the eMBB service type based on the first energy efficiency and the second energy efficiency.

[0130] In the fourth example, the calculation formula of the first energy efficiency is:

[0131]

[0132] Among them, EE DV First energy efficiency, DV RLC_UL is the RLC layer uplink traffic, QF DV_UL 1-RLC layer uplink retransmission rate, DV RLC_DL is the downlink traffic volume of the RLC layer, QF DV_DL is 1-RLC layer downlink retransmission rate, (1-η)*EC is the first effective energy consumption, EC is the effective energy consumption of the equipment, η is the proportion of renewable energy input time; where QF DV_UL and QF DV_DL The combination becomes the first quality factor, DV RLC_UL and DV RLC_DL The combination becomes the first business output.

[0133] The calculation formula for the second energy efficiency is:

[0134]

[0135] Among them, EE COV is the second energy efficiency, COV is the second service output, i.e., the base station signal coverage area; QF CoV is the second quality factor, i.e., the coverage quality factor; (1-η)*EC is the first effective energy consumption, EC is the effective energy consumption of the equipment, and η is the proportion of renewable energy input time.

[0136] By performing weighted calculation on the first energy efficiency and the second energy efficiency, the overall energy efficiency of the network in the eMBB service type is obtained.

[0137] When the main scenario is coverage, if there are multiple RATs at the same site, only the low-frequency band energy consumption is calculated. In the fifth example, there are 2.1GHz and 900MHz 5G base stations at the same site. The low-frequency band can cover a longer distance, and the coverage is mainly the output energy of the 900M base station.

[0138] S205. Compare the average value of the first energy efficiency and the average value of the second energy efficiency of the eMBB service type in different wireless networks, and obtain a comparison result; and / or, determine the average values ​​of the two first energy efficiencies corresponding to the eMBB service type based on any two wireless networks, calculate a comparison coefficient based on the distribution of uplink traffic and downlink traffic of base stations corresponding to the two wireless networks, and compare and calculate the average values ​​of the two first energy efficiencies based on the comparison coefficient, and determine a comparison result; and / or, compare the unit energy efficiency of the average value of the first energy efficiency and the unit energy efficiency of the average value of the second energy efficiency of the eMBB service type in the same wireless network based on a preset weight, and obtain a comparison result;

[0139] The calculation formula for the average value of the first energy efficiency and the average value of the second energy efficiency is:

[0140]

[0141] Among them, EE DV_Total is the average value of the first energy efficiency, is the first energy efficiency when the i-th main scene is capacity type, DV i It is the first service output when the i-th main scenario is capacity type; EE COV_Total is the average value of the second energy efficiency, is the second energy efficiency when the i-th main scene is coverage type, COV i It is the second service output when the i-th main scene is of overlay type.

[0142] In the sixth exemplary embodiment, an average value of two first energy efficiencies corresponding to the eMBB service type is determined based on any two wireless networks, a comparison coefficient is calculated based on the distribution of uplink traffic and downlink traffic of base stations corresponding to the two wireless networks, and the average values ​​of the two first energy efficiencies are compared and calculated based on the comparison coefficient, and the comparison result may be:

[0143] Select the energy consumption EC of the base station where the traffic is uplink only in a certain period of time and / or the uplink traffic accounts for more than 80% DL , are all energy-consuming ECs with downstream traffic and / or downstream traffic accounting for more than 80% UL ; Calculate the ratio γ = EC DL / EC UL .

[0144] in:

[0145] Uplink traffic ratio = RLC layer uplink traffic / (RLC layer uplink traffic + RLC layer downlink traffic)

[0146] Downlink traffic ratio = RLC layer downlink traffic volume / (RLC layer uplink traffic volume + RLC layer downlink traffic volume).

[0147] In the sixth example, the downlink traffic proportions of the two wireless networks are ε1 of the first wireless network and ε2 of the second wireless network, and both wireless networks belong to the eMBB service type and the main scenario is capacity type. Then, the average values ​​of the first energy efficiencies corresponding to the two wireless networks are EE of the first wireless network and EE of the second wireless network. DV_Total_1 and EE of the second wireless network DV Total 2. Taking the first wireless network as a benchmark, the average value of the first energy efficiency of the second wireless network is uniformly adjusted, and the formula is:

[0148]

[0149] The adjusted average value of the first energy efficiency of the second wireless network is compared with the average value of the first energy efficiency of the first wireless network to obtain a comparison result.

[0150] Where, γ is the ratio of energy consumption of uplink traffic to downlink traffic, ε1 is the proportion of downlink traffic of the first wireless network, ε2 is the proportion of downlink traffic of the second wireless network, and EE DV_Total_2 is the average value of the first energy efficiency of the second wireless network.

[0151] In the seventh example, the unit energy efficiency of the average value of the first energy efficiency and the unit energy efficiency of the average value of the second energy efficiency of the eMBB service type in the same wireless network are compared based on the preset weight, and the comparison result is obtained, which may be:

[0152] Get the average value of the first energy efficiency EE of the wireless network DV_Total and the average value of the second energy efficiency EE COV_Total , the units are GB / Kwh and km respectively 2 / KwhIn the same network, it is impossible to form an overall energy efficiency benchmark analysis, and the derivatives are used to represent the energy efficiency per GB and per km 2 The energy consumed is:

[0153]

[0154] Use the preset weight values ​​α and β for comparison, and the comparison formula is:

[0155]

[0156] Among them, α and β are the energy consumption per GB and per km respectively. 2 Energy consumption weight value, ECeMBB_unit For the comparison results of the calculation, EE DV_Total is the average value of the first energy efficiency, EE COV_Total is the average value of the second energy efficiency.

[0157] S206. When the service type is a uRLLC service type, determine a third quality factor corresponding to the uRLLC service type; determine the network reliability and end-to-end delay corresponding to the uRLLC service type based on the performance data, and determine the third service output corresponding to the uRLLC service type; determine the slice energy consumption corresponding to the uRLLC service type based on the network slicing mode of the uRLLC service type, and determine the corresponding second effective energy consumption based on the slice energy consumption; determine the ratio of the product of the third quality factor and the third service output to the second effective energy consumption as the third energy efficiency, and determine the third energy efficiency as the target energy efficiency corresponding to the uRLLC service type;

[0158] In this embodiment, the main performance of the uRLLC service type is end-to-end delay and network reliability. The third service output determined based on network reliability and end-to-end delay is: network reliability / end-to-end delay, expressed as: P rel / T; and the network reliability and end-to-end delay are both actual measured values, so the third quality factor is 1.

[0159] In this embodiment, the network slicing methods can be divided into three forms: 5QI, RB resource reservation and carrier isolation; the slices based on 5QI are divided into three forms according to the slice traffic ratio θ uRLLC_5QI Multiply the energy consumption of the device by the equivalent slice energy consumption, based on the proportion of reserved RBs to total RBs θ uRLLC_RB Multiply the device energy consumption by the equivalent slice energy consumption, based on the bandwidth ratio θ of carrier isolation uRLLC_BWP Multiply the device energy consumption by the equivalent slice energy consumption.

[0160] In this embodiment, the slice energy efficiency calculation formula of uRLLC is:

[0161]

[0162] or

[0163] or

[0164] Among them, EE uRLLC is the slice energy efficiency, i.e. the third energy efficiency; P rel / T is the third business output, (1-η)*EC is the first effective energy consumption, EC is the effective energy consumption of the equipment, η is the proportion of renewable energy input time; θ uRLLC_5QI *(1-η)*EC*T is the slice energy consumption based on 5QI slices, θ uRLLC_RB*(1-η)*EC*T is the slice energy consumption based on RB resource reserved slices, θ uRLLC_BWP *(1-η)*EC*T is the slice energy consumption based on carrier isolation slices, where the slice energy consumption is the second effective energy consumption.

[0165] S207. When the service type is an mMTC service type, determine a third quality factor corresponding to the mMTC service type; determine the number of supported connections corresponding to the mMTC service type based on the performance data, and determine a fourth service output corresponding to the mMTC service type; determine a slice energy consumption corresponding to the mMTC service type based on a network slicing method of the mMTC service type, and determine a corresponding third effective energy consumption based on the slice energy consumption; determine a ratio of a product of the third quality factor and the fourth service output to the third effective energy consumption as a fourth energy efficiency, and determine the fourth energy efficiency as a target energy efficiency corresponding to the mMTC service type;

[0166] In this embodiment, the main characteristic of the mMTC service type is the number of supported connections. The number of supported connections is output as the fourth service, represented by N mMTC ; Since the number of supported connections is an actual measured value, the third quality factor corresponding to the mMTC service type is 1.

[0167] In this embodiment, the mMTC service type also calculates energy efficiency based on three different network slicing methods, and the calculation formula is:

[0168]

[0169] or

[0170] or

[0171] Among them, EE mMTC N is the slice energy efficiency of the mMTC service type, that is, the fourth energy efficiency; mMTC is the fourth business output, (1-η)*EC is the first effective energy consumption, EC is the effective energy consumption of the equipment, η is the proportion of renewable energy input time; θ uRLLC_5QI *(1-η)*EC*T is the slice energy consumption based on 5QI slices, θ uRLLC_RB *(1-η)*EC*T is the slice energy consumption based on RB slices, θ uRLLC_BWP *(1-η)*EC*T is the slice energy consumption based on carrier isolation slices, where the slice energy consumption is the second effective energy consumption.

[0172] S208. Determine the planned business output, planned quality factor and planned effective energy consumption based on the preset planning data, and calculate the predicted energy efficiency corresponding to the planned business output, planned quality factor and planned effective energy consumption based on the preset energy efficiency formula; perform fitting calculation based on the preset planning data and the predicted energy efficiency, and determine the fitting curve; predict and determine the predicted business output based on the fitting curve, and calculate and determine the predicted energy consumption based on the predicted business output.

[0173] In this embodiment, the preset planning data is determined by collecting network environment, equipment deployment category and configuration, service distribution and type, energy consumption indicators and planned usage data, and the planned service output, planned quality factor and planned effective energy consumption are determined based on the preset planning data; the predicted energy efficiency is calculated and determined through the preset energy efficiency formula; the preset energy efficiency formula is: planned service output*planned quality factor / planned effective energy consumption.

[0174] like Figure 4 As shown, in the eighth example, in the preset planning data, the network environment includes: population density, planning scenario, climate and terrain; equipment deployment type and configuration include: macro and micro, indoor distribution, channel, frequency band, manufacturer and energy saving; business distribution and types include: business characteristics, business guarantee, load, distribution and user distribution. Based on the preset planning data, the energy efficiency corresponding to a single station is determined, and a fitting curve associated with energy efficiency of a specific network environment, a specific equipment type and configuration, and a specific business distribution and type is formed through three-dimensional clustering; planning new sites, predicting the business output of the planned sites, where the business output can be business volume or coverage area; combining the planned site attributes to find the corresponding fitting energy efficiency curve function, where the planned site attributes can be site environment, configuration and business type; based on the fitting energy efficiency curve function, the predicted business output is determined, and the predicted energy consumption after the base station is built can be accurately calculated. At the same time, an overall estimate of the future wireless network energy efficiency and energy consumption change trend can be made, including 5G energy consumption cost and energy consumption.

[0175] The population density can be determined based on the regional type, including: urban areas, county towns, suburbs and rural areas; planning scenarios include but are not limited to: campuses, hospitals and transportation hubs; climate is limited by seasons, including spring, summer, autumn and winter, and can also be determined based on the climate range of the geographical location; terrain includes but is not limited to mountainous areas, plains or plateaus. In the equipment deployment type and configuration, macro and micro include: macro base stations, micro base stations and indoor distribution; indoor distribution can be: indoor distributed antenna system (DAS) or distributed indoor system (DIS); channels, that is, wireless communication channels or channels, can be divided into: 4TR, 32TR, 64TR types of channels; frequency bands can be: 900M, 2.1G or 3.5G; manufacturers determine the manufacturer information of the equipment based on actual planning data; energy-saving types include: carrier shutdown type and symbol shutdown type. In terms of service distribution and types, the characteristics of services can be divided into two types: uplink-based services and downlink-based services; service assurance includes: service quality in 5G networks, namely 5QI, where 5QI includes two different service quality categories: guaranteed bit rate (GBR) and non-guaranteed bit rate (non GBR); load can be the utilization efficiency of physical resource blocks (PRB); distribution type can be 24-hour distribution; user distribution is determined based on the distance of the user.

[0176] The present application provides a method for evaluating the energy efficiency of a wireless network. The method includes: obtaining network performance data of a base station, energy consumption data of a device, and a service type corresponding to a wireless network service; determining a corresponding quality factor based on the service type, determining service output based on performance data, and determining effective energy consumption of the device based on energy consumption data; and determining a target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and service output to the effective energy consumption. Energy efficiency calculation is performed for three different service types. When the service type is the eMBB service type, the quality factor and service output are determined for the main scenario type of the application, and the energy efficiency corresponding to the capacity type and the coverage type are calculated, and the average value of the energy efficiency is calculated respectively. By comparing the average value of the energy efficiency of the two main scenarios of the eMBB service type in different wireless networks, the energy efficiency comparison in the eMBB type is realized; at the same time, when calculating the effective energy consumption, the proportion of the input time of renewable energy in the energy consumption of the equipment is obtained, and the renewable energy is excluded from the energy consumption calculation, so as to obtain more accurate effective energy consumption of the equipment, eliminate the influence of renewable energy on energy efficiency evaluation, and increase the accuracy of energy efficiency evaluation; when the task type is the uRLLC service type and the mMTC service type, the slice energy consumption is calculated according to different network slicing methods to ensure the accuracy of effective energy consumption; by considering the quality factors of performance evaluation when multiple service types are applied to the construction of wireless networks, and performing performance evaluation according to the quality factors of different service types and the corresponding service output and effective energy consumption; the technical effect of improving the accuracy of energy efficiency evaluation is achieved, thereby solving the technical problem of low accuracy of energy efficiency evaluation in the prior art.

[0177] Figure 5 This is a schematic diagram of the structure of the wireless network energy efficiency evaluation device provided in the embodiment of the present application. The device of this embodiment can be in the form of software and / or hardware. Figure 5 As shown, a wireless network energy efficiency evaluation device 500 provided in an embodiment of the present application includes: an acquisition module 501, a processing module 502 and a determination module 503.

[0178] The acquisition module 501 is used to acquire the network performance data of the base station, the energy consumption data of the device, and the service type corresponding to the wireless network service;

[0179] A processing module 502 is used to determine a corresponding quality factor based on a service type, determine a service output based on performance data, and determine an effective energy consumption of a device based on energy consumption data;

[0180] The determination module 503 is used to determine the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption.

[0181] In a possible implementation, the device is further used for:

[0182] Determine whether the service type is an eMBB service type, and if so, determine the corresponding main scenario type and quality factor based on the wireless network service;

[0183] Determine the service output based on the main scenario type, quality factors and performance data;

[0184] The preset renewable energy usage time ratio of the device is determined based on the energy consumption data, and the first effective energy consumption of the device is determined based on the preset renewable energy usage time ratio.

[0185] In a possible implementation, the device is further used for:

[0186] When the main scenario type is determined to be capacity type based on the wireless network service, a corresponding first quality factor is determined based on an RLC layer uplink retransmission rate and an RLC layer downlink retransmission rate corresponding to the eMBB service type;

[0187] When the main scenario type is determined to be coverage type based on the wireless network service, a coverage quality factor acquisition method of the eMBB service type is obtained, and a second quality factor corresponding to the coverage type is determined based on the acquisition method.

[0188] In a possible implementation, the device is further used for:

[0189] Determine based on the performance data that when the eMBB service type is a capacity type in the primary scenario, determine the service volume of the RLC layer, and determine the first service output based on the service volume;

[0190] Based on the performance data, when the eMBB service type is a coverage type in the main scenario, the base station signal coverage area corresponding to the coverage type is determined, and the second service output is determined based on the base station signal coverage area.

[0191] In a possible implementation, the device is further used for:

[0192] When the service type is a uRLLC service type, determining a third quality factor corresponding to the uRLLC service type;

[0193] Determine the network reliability and end-to-end delay corresponding to the uRLLC service type based on the performance data, and determine the third service output corresponding to the uRLLC service type;

[0194] The network slicing method based on the uRLLC service type determines the slice energy consumption corresponding to the uRLLC service type, and determines the corresponding second effective energy consumption based on the slice energy consumption.

[0195] In a possible implementation, the device is further used for:

[0196] When the service type is an mMTC service type, determining a third quality factor corresponding to the mMTC service type;

[0197] Determine the number of supported connections corresponding to the mMTC service type based on the performance data, and determine a fourth service output corresponding to the mMTC service type;

[0198] The network slicing method based on the mMTC service type determines the slice energy consumption corresponding to the mMTC service type, and determines the corresponding third effective energy consumption based on the slice energy consumption.

[0199] In a possible implementation, the device is further used for:

[0200] When the service type is an eMBB service type, determining a first energy efficiency based on a ratio of a product of a first quality factor and a first service output to a first effective energy consumption;

[0201] Determining a second energy efficiency based on a ratio of a product of a second quality factor and a second service output to the first effective energy consumption;

[0202] Determine a target energy efficiency corresponding to the eMBB service type based on the first energy efficiency and the second energy efficiency;

[0203] When the service type is a uRLLC service type, a ratio of a product of the third quality factor and the third service output to the second effective energy consumption is determined as a third energy efficiency, and the third energy efficiency is determined as a target energy efficiency corresponding to the uRLLC service type;

[0204] When the service type is the mMTC service type, the ratio of the product of the third quality factor and the fourth service output to the third effective energy consumption is determined as the fourth energy efficiency, and the fourth energy efficiency is determined as the target energy efficiency corresponding to the mMTC service type.

[0205] In a possible implementation, the device is further used for:

[0206] Comparing an average value of the first energy efficiency and an average value of the second energy efficiency of the eMBB service type in different wireless networks, and obtaining a comparison result;

[0207] Determine an average value of two first energy efficiencies corresponding to the eMBB service type based on any two wireless networks, calculate a comparison coefficient based on the distribution of uplink traffic and downlink traffic of base stations corresponding to the two wireless networks, and compare and calculate the average values ​​of the two first energy efficiencies based on the comparison coefficient, and determine a comparison result;

[0208] The unit energy efficiency of the average value of the first energy efficiency and the unit energy efficiency of the average value of the second energy efficiency of the eMBB service type in the same wireless network are compared based on the preset weight, and a comparison result is obtained.

[0209] In a possible implementation, the device is further used for:

[0210] Determine the planned business output, planned quality factor and planned effective energy consumption based on the preset planning data, and calculate the predicted energy efficiency corresponding to the planned business output, planned quality factor and planned effective energy consumption based on the preset energy efficiency formula;

[0211] Perform fitting calculation based on preset planning data and predicted energy efficiency, and determine the fitting curve;

[0212] The predicted business output is predicted and determined based on the fitting curve, and the predicted energy consumption is calculated and determined based on the predicted business output.

[0213] The present application provides a wireless network energy efficiency evaluation device. The device includes: an acquisition module, which is used to acquire the network performance data of the base station, the energy consumption data of the device, and the service type corresponding to the wireless network service; a processing module, which is used to determine the corresponding quality factor based on the service type, determine the service output based on the performance data, and determine the effective energy consumption of the device based on the energy consumption data; a determination module, which is used to determine the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption. Energy efficiency calculation is performed for three different service types. When the service type is the eMBB service type, the quality factor and service output are determined for the main scenario type of the application, and the energy efficiency corresponding to the capacity type and the coverage type are calculated, and the average value of the energy efficiency is calculated respectively. By comparing the average value of the energy efficiency of the two main scenarios of the eMBB service type in different wireless networks, the energy efficiency comparison in the eMBB type is realized; at the same time, when calculating the effective energy consumption, the proportion of the input time of renewable energy in the energy consumption of the equipment is obtained, and the renewable energy is excluded from the energy consumption calculation, so as to obtain more accurate effective energy consumption of the equipment, eliminate the influence of renewable energy on energy efficiency evaluation, and increase the accuracy of energy efficiency evaluation; when the task type is the uRLLC service type and the mMTC service type, the slice energy consumption is calculated according to different network slicing methods to ensure the accuracy of effective energy consumption; by considering the quality factors of performance evaluation when multiple service types are applied to the construction of wireless networks, and performing performance evaluation according to the quality factors of different service types and the corresponding service output and effective energy consumption; the technical effect of improving the accuracy of energy efficiency evaluation is achieved, thereby solving the technical problem of low accuracy of energy efficiency evaluation in the prior art.

[0214] Figure 6 The hardware structure diagram of the wireless network energy efficiency evaluation device provided in the embodiment of the present application. Figure 6 As shown, the wireless network energy efficiency evaluation device 600 includes:

[0215] Processor 601 and memory 602;

[0216] Memory stores computer-executable instructions;

[0217] The processor executes the computer-executable instructions stored in the memory 602 , so that the wireless network energy efficiency evaluation device executes the wireless network energy efficiency evaluation method as described above.

[0218] It should be understood that the processor 601 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The memory 602 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a disk or an optical disk, etc.

[0219] The embodiment of the present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement a wireless network energy efficiency evaluation method.

[0220] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0221] It should be further noted that, although the various steps in the flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0222] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present application can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0223] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application may be integrated into one unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

[0224] If the integrated unit / module is implemented in the form of hardware, the hardware may be a digital circuit, an analog circuit, etc. The physical implementation of the hardware structure includes but is not limited to transistors, memristors, etc. If not specifically stated, the processor may be any appropriate hardware processor, such as a CPU, a GPU, an FPGA, a DSP, and an ASIC, etc. If not specifically stated, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc.

[0225] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0226] In the above embodiments, the description of each embodiment has its own emphasis. For the part not described in detail in a certain embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0227] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0228] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A wireless network energy efficiency evaluation method, characterized in that: include: Obtain network performance data of base stations, energy consumption data of equipment, and service types corresponding to wireless network services; Determine a corresponding quality factor based on the service type, determine a service output based on the performance data, and determine an effective energy consumption of the device based on the energy consumption data; The target energy efficiency corresponding to the service type is determined based on a ratio of a product of the quality factor and the service output to the effective energy consumption.

2. The method according to claim 1, characterized in that The determining the corresponding quality factor based on the service type, determining the service output based on the performance data, and determining the effective energy consumption of the device based on the energy consumption data includes: Determine whether the service type is an eMBB service type, and if so, determine a corresponding main scenario type and the quality factor based on the wireless network service; Determining the service output based on the main scenario type, the quality factor, and the performance data; The preset renewable energy usage time ratio of the device is determined based on the energy consumption data, and the first effective energy consumption of the device is determined based on the preset renewable energy usage time ratio.

3. The method according to claim 2, characterized in that The determining the corresponding main scenario type and the quality factor based on the wireless network service includes: When it is determined that the main scenario type is capacity type based on the wireless network service, determining a corresponding first quality factor based on an RLC layer uplink retransmission rate and an RLC layer downlink retransmission rate corresponding to the eMB B service type; When it is determined that the main scenario type is a coverage type based on the wireless network service, a coverage quality factor acquisition method of the eMB B service type is acquired, and a second quality factor corresponding to the coverage type is determined based on the acquisition method.

4. The method according to claim 3, characterized in that The determining the service output based on the main scenario type, the quality factor, and the performance data includes: Determine the eMBB service type based on the performance data when the main scenario is the capacity type, determine the service volume of the RLC layer, and determine a first service output based on the service volume; Determine based on the performance data that when the eMBB service type is the coverage type in the main scenario, the base station signal coverage area corresponding to the coverage type, and determine the second service output based on the base station signal coverage area.

5. The method according to claim 2, characterized in that: The determining of the corresponding quality factor based on the service type, determining the service output based on the performance data, and determining the effective energy consumption of the device based on the energy consumption data further includes: When the service type is a uRLLC service type, determining a third quality factor corresponding to the uRLLC service type; Determine the network reliability and end-to-end delay corresponding to the uRLLC service type based on the performance data, and determine a third service output corresponding to the uRLLC service type; The slice energy consumption corresponding to the uRLLC service type is determined based on the network slicing method of the uRLLC service type, and the corresponding second effective energy consumption is determined based on the slice energy consumption.

6. The method according to claim 5, characterized in that The determining of the corresponding quality factor based on the service type and determining the service output based on the performance data further includes: When the service type is an mMTC service type, determining a third quality factor corresponding to the mMTC service type; Determine the number of supported connections corresponding to the mMTC service type based on the performance data, and determine a fourth service output corresponding to the mMTC service type; The slice energy consumption corresponding to the mMTC service type is determined based on the network slicing method of the mMTC service type, and the corresponding third effective energy consumption is determined based on the slice energy consumption.

7. The method according to any one of claims 2 to 6, characterized in that The determining the energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption includes: When the service type is the eMBB service type, determining a first energy efficiency based on a ratio of a product of the first quality factor and the first service output to the first effective energy consumption; determining a second energy efficiency based on a ratio of a product of the second quality factor and the second service output to the first effective energy consumption; Determine the target energy efficiency corresponding to the eMBB service type based on the first energy efficiency and the second energy efficiency; When the service type is the uRLLC service type, determining a ratio of a product of the third quality factor and the third service output to the second effective energy consumption as a third energy efficiency, and determining the third energy efficiency as the target energy efficiency corresponding to the uRLLC service type; When the service type is the mMTC service type, a ratio of a product of the third quality factor and the fourth service output to the third effective energy consumption is determined as a fourth energy efficiency, and the fourth energy efficiency is determined as the target energy efficiency corresponding to the mMTC service type.

8. The method according to claim 7, characterized in that After determining the target energy efficiency corresponding to the eMBB service type based on the first energy efficiency and the second energy efficiency, the method further includes any one of the following: Comparing an average value of the first energy efficiency and an average value of the second energy efficiency of the eMBB service type in different wireless networks, and obtaining a comparison result; Determine an average value of two first energy efficiencies corresponding to the eMBB service type based on any two of the wireless networks, calculate a comparison coefficient based on the distribution of uplink traffic and downlink traffic of the base station corresponding to the two wireless networks, and compare and calculate the average values ​​of the two first energy efficiencies based on the comparison coefficient, and determine the comparison result; The unit energy efficiency of the average value of the first energy efficiency and the unit energy efficiency of the average value of the second energy efficiency of the eMBB service type in the same wireless network are compared based on a preset weight, and the comparison result is obtained.

9. The method according to claim 1, characterized in that: After determining the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption, the method further includes: Determine the planned business output, the planned quality factor and the planned effective energy consumption based on the preset planning data, and calculate the predicted energy efficiency corresponding to the planned business output, the planned quality factor and the planned effective energy consumption based on the preset energy efficiency formula; Performing a fitting calculation based on the preset planning data and the predicted energy efficiency, and determining a fitting curve; The predicted business output is predicted and determined based on the fitting curve, and the predicted energy consumption is calculated and determined based on the predicted business output.

10. A wireless network energy efficiency evaluation device, characterized in that: include: An acquisition module is used to obtain network performance data of base stations, energy consumption data of devices, and service types corresponding to wireless network services; A processing module, configured to determine a corresponding quality factor based on the service type, determine a service output based on the performance data, and determine an effective energy consumption of the device based on the energy consumption data; A determination module is used to determine the target energy efficiency corresponding to the service type based on the ratio of the product of the quality factor and the service output to the effective energy consumption.

11. A wireless network energy efficiency evaluation device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the wireless network energy efficiency evaluation method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the wireless network energy efficiency evaluation method according to any one of claims 1 to 9.

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