WO2024093828A1

WO2024093828A1 - Network energy efficiency determining method and apparatus, and storage medium

Info

Publication number: WO2024093828A1
Application number: PCT/CN2023/127163
Authority: WO
Inventors: 金雨超; 李�一; 郑雨婷; 王静云; 李德屹; 龙青良; 李菲; 曹丽娟; 贾玉玮; 程新洲
Original assignee: 中国联合网络通信集团有限公司
Priority date: 2022-10-31
Filing date: 2023-10-27
Publication date: 2024-05-10
Also published as: CN115695232A

Abstract

The present application relates to the technical field of communications, and provides a network energy efficiency determining method and apparatus, and a storage medium, capable of improving the accuracy of network energy efficiency. The method comprises: determining first data of a target slice in a target time period and the reliability of the target slice in the target time period, wherein the first data comprises at least one of energy consumption, mean latency, and traffic, the reliability is used for representing the transmission success rate of a data packet transmitted between a target access network device and a target terminal device, and the target access network device and the target terminal device are both devices in the target slice; and determining the network energy efficiency of the target slice in the target time period according to the first data and the reliability. The embodiments of the present application are used in a process of determining network energy efficiency.

Description

Network energy efficiency determination method, device and storage medium

This application claims priority to the Chinese patent application filed with the State Intellectual Property Office on October 31, 2022, with application number 202211366273.9 and application name “Network Energy Efficiency Determination Method, Device and Storage Medium”, all contents of which are incorporated by reference in this application.

Technical Field

The present application relates to the field of communication technology, and in particular to a method, device and storage medium for determining network energy efficiency.

Background technique

In communication networks, network energy efficiency can reflect the energy utilization efficiency of the network and plays a key role in helping operators obtain the actual situation of the network.

At present, the determination of network energy efficiency is mainly based on indicators such as energy consumption, latency, and traffic. However, the above indicators cannot fully reflect the actual situation of the network, which leads to the network energy efficiency determined by the above method cannot accurately reflect the actual situation of the network, resulting in low accuracy of network energy efficiency.

Summary of the invention

The present application provides a method, device and storage medium for determining network energy efficiency, which can improve the accuracy of network energy efficiency.

In order to achieve the above objectives, this application adopts the following technical solutions:

In a first aspect, the present application provides a method for determining network energy efficiency, the method comprising: determining first data of a target slice within a target time period, and the reliability of the target slice within the target time period; the first data comprises: at least one of energy consumption, average delay and traffic; reliability is used to characterize the transmission success rate of data packets transmitted between a target access network device and a target terminal device; the target access network device and the target terminal device are both devices in the target slice; based on the first data and reliability, determining the network energy efficiency of the target slice within the target time period.

In a possible implementation, determining the reliability of a target slice within a target time period includes: obtaining the number of first data packets of the target slice within the target time period, and any one of the number of second data packets and the number of third data packets; the first data packet is used to characterize a data packet transmitted based on a target interface; the second data packet is used to characterize a data packet successfully transmitted based on the target interface; the number of third data packets is used to characterize that the delay in the second data packet is less than or equal to a preset The number of data packets in a time period; the target interface is the interface between the target access network device and the target terminal device; based on the number of first data packets, and any one of the number of second data packets and the number of third data packets, the reliability of the target slice within the target time period is determined.

In a possible implementation, the number of first data packets includes: the number of uplink first data packets and the number of downlink first data packets; the uplink first data packets are data packets sent by the target terminal device; the downlink first data packets are data packets sent by the access network device; the number of second data packets includes: the number of uplink second data packets and the number of downlink second data packets; the uplink second data packets are data packets received by the target terminal device; the downlink second data packets are data packets received by the target access network device; the number of third data packets includes: the number of uplink third data packets and the number of downlink third data packets; the uplink third data packets are data packets in the uplink second data packets with a delay less than or equal to the first preset time period; the number of downlink third data packets are data packets in the downlink second data packets with a delay less than or equal to the second preset time period.

In one possible implementation, reliability satisfies the following formula:
Re＝(DLA2/DLA1)×(ULA2/ULA1)

Wherein, Re is reliability; DLA1 is the number of downlink first data packets; DLA2 is the number of downlink second data packets; ULA1 is the number of uplink first data packets; ULA2 is the number of uplink second data packets.

In one possible implementation, reliability satisfies the following formula:
Re＝(DLA2+ULA2)/(DLA1+ULA1)

In one possible implementation, reliability satisfies the following formula:
Re＝(DLA3/DLA1)×(ULA3/ULA1)

Wherein, Re is reliability; DLA1 is the number of first downlink data packets; DLA3 is the number of third downlink data packets; ULA1 is the number of first uplink data packets; ULA3 is the number of third uplink data packets.

In one possible implementation, reliability satisfies the following formula:
Re＝(DLA3+ULA3)/(DLA1+ULA1)

In one possible implementation, when the first data includes energy consumption, the network energy efficiency of the target slice within the target time period is determined based on the first data and reliability, including: determining the ratio of reliability to energy consumption as the network energy efficiency.

In one possible implementation, when the first data includes energy consumption and average delay, the network energy efficiency of the target slice within the target time period is determined based on the first data and reliability, including: determining the ratio of reliability to average delay as a first value; determining the ratio of the first value to energy consumption as network energy efficiency.

In one possible implementation, when the first data includes energy consumption and traffic, and the traffic includes: uplink traffic and downlink traffic, the network energy efficiency of the target slice within the target time period is determined based on the first data and reliability, including: performing a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determining the product of the reliability and the second value as a third value; determining the ratio of the third value to the energy consumption as the network energy efficiency.

In one possible implementation, when the first data includes energy consumption, average delay, and traffic, and the traffic includes: uplink traffic and downlink traffic, the network energy efficiency of the target slice within the target time period is determined based on the first data and reliability, including: performing a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determining the product of the reliability and the second value, and the ratio of the product to the average delay is a fourth value; determining the ratio of the fourth value to energy consumption as the network energy efficiency.

In a second aspect, the present application provides a network energy efficiency determination device, which includes: a processing unit; a processing unit, used to determine the first data of a target slice within a target time period, and the reliability of the target slice within the target time period; the first data includes: at least one of energy consumption, average delay and traffic; reliability is used to characterize the transmission success rate of data packets transmitted between a target access network device and a target terminal device; the target access network device and the target terminal device are both devices in the target slice; the processing unit is also used to determine the network energy efficiency of the target slice within the target time period based on the first data and reliability.

In a possible implementation, the network energy efficiency determination device also includes: a communication unit; the communication unit is further used to obtain the number of first data packets of the target slice within the target time period, and any one of the number of second data packets and the number of third data packets; the first data packet is used to characterize the data packet transmitted based on the target interface; the second data packet is used to characterize the data packet successfully transmitted based on the target interface; the number of third data packets is used to characterize the number of data packets in the second data packet whose delay is less than or equal to the preset time period; the target interface is an interface between the target access network device and the target terminal device; the processing unit is also used based on the number of the first data packet, and Any one of the number of the second data packets and the number of the third data packets determines the reliability of the target slice within the target time period.

In a possible implementation, when the first data includes energy consumption, the processing unit It is also used to determine the ratio of reliability to energy consumption as network energy efficiency.

In a possible implementation, when the first data includes energy consumption and average delay, the processing unit is further used to determine that the ratio of reliability to average delay is a first value; the processing unit is further used to determine that the ratio of the first value to energy consumption is network energy efficiency.

In one possible implementation, when the first data includes energy consumption and traffic, and the traffic includes: uplink traffic and downlink traffic, the processing unit is further used to perform a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determine the product of the reliability and the second value as a third value; the processing unit is also used to determine the ratio of the third value to the energy consumption as the network energy efficiency.

In one possible implementation, when the first data includes energy consumption, average delay and traffic, and the traffic includes: uplink traffic and downlink traffic, the processing unit is further used to perform weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determine the product of the reliability and the second value, and the ratio of the product to the average delay is a fourth value; the processing unit is also used to determine the ratio of the fourth value to the energy consumption as the network energy efficiency.

In a third aspect, the present application provides a network energy efficiency determination device, the device comprising: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is used to run a computer program or instructions to implement the network energy efficiency determination method as described in the first aspect and any possible implementation method of the first aspect.

In a fourth aspect, the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal, the terminal executes the network energy efficiency determination method described in the first aspect and any possible implementation of the first aspect.

In a fifth aspect, the present application provides a computer program product comprising instructions. When the computer program product runs on a network energy efficiency determination device, the network energy efficiency determination device executes the network energy efficiency determination method as described in the first aspect and any possible implementation of the first aspect.

In a sixth aspect, the present application provides a chip, the chip comprising a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run a computer program or instructions to implement the network energy efficiency determination method as described in the first aspect and any possible implementation method of the first aspect.

Specifically, the chip provided in the present application also includes a memory for storing computer programs or instructions.

The above technical solution brings at least the following beneficial effects: the network energy efficiency determination method provided by the present application can determine the first data (i.e., energy consumption, At least one of the average delay and flow) and reliability, and determine the network energy efficiency of the target slice in the target time period according to the first data and reliability determined above. Therefore, the network energy efficiency determination method provided by the present application can combine indicators such as energy consumption, delay, and flow with reliability, and jointly serve as data support for determining network energy efficiency, so that the determination of network energy efficiency can more comprehensively and accurately reflect the actual situation of the network, thereby improving the accuracy of network energy efficiency.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a structural diagram of a communication system provided in an embodiment of the present application;

FIG2 is a flow chart of a method for determining network energy efficiency provided in an embodiment of the present application;

FIG3 is a flow chart of another method for determining network energy efficiency provided in an embodiment of the present application;

FIG4 is a flow chart of another method for determining network energy efficiency provided in an embodiment of the present application;

FIG5 is a schematic diagram of the structure of a network energy efficiency determination device provided in an embodiment of the present application;

FIG6 is a schematic diagram of the structure of another network energy efficiency determination device provided in an embodiment of the present application.

Detailed ways

The network energy efficiency determination method, device and storage medium provided in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

The term "and/or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and/or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

In the description of the present application, unless otherwise specified, “plurality” means two or more.

The following explains the terms involved in the embodiments of the present application to facilitate the reader's understanding.

1. Ultra-reliable low-latency communication (URLLC)

URLLC has the characteristics of ultra-low latency and ultra-high reliability. URLLC can be widely used in industrial control scenarios, equipment automation scenarios, Internet of Vehicles scenarios, smart grid scenarios, and remote surgery scenarios.

In some examples, URLLC can make the uplink and downlink delays of service transmission between access network equipment and terminal equipment (i.e., the wireless side) less than or equal to 0.5 milliseconds (ms), and URLLC can also make the reliability of the above service transmission reach the 10-5 level.

2. Network energy efficiency (NEE)

Network energy efficiency refers to a key performance indicator (KPI) used to reflect the energy efficiency of the network.

In a possible implementation, the above network energy efficiency may include network energy efficiency based on latency and network energy efficiency based on latency and traffic. The network energy efficiency based on latency and network energy efficiency based on latency and traffic are described below respectively:

1.1 Network Energy Efficiency Based on Latency

Delay-based network energy efficiency refers to the network energy efficiency determined based on the average delay of the network.

For example, taking the latency-based network energy efficiency of network slice #1 (e.g., URLLC network slice) as an example, the latency-based network energy efficiency of network slice #1 can satisfy the following formula 1:

Wherein, EE _{URLLLC,Latency1} is the latency-based network energy efficiency of network slice #1 in time period #1. P _{URLLLC,Latency1} is the inverse of the average latency of network slice #1 in time period #1. Network slice mean latency1 is the average latency of network slice #1 in time period #1. _{EC URLLLC,Latency1} is the energy consumption of network slice #1 in time period #1.

It can be seen from the above formula 1 that the above P _{URLLLC,Latency1} satisfies the following formula 2:

Optionally, the above Network slice mean latency 1 may satisfy the following formula 3:
Network slice mean latency1＝DelayE2EULNs1+DelayE2EDLNs1 Formula 3

Where DelayE2EULNs1 is the average uplink time of network slice #1 in time period #1. DelayE2EDLNs1 is the average downlink delay of network slice #1 in time period #1.

In one example, the above average delay can be the average value of the end-to-end user plane delay of network slice #1.

Wherein, DelayE2EULNs1 is the average uplink delay of network slice #1 in time period #1. DelayE2EDLNs1 is the average downlink delay of network slice #1 in time period #1.

It should be pointed out that the energy consumption of different types of network slices can be calculated in the same way.

In one possible implementation, the computing device may count the delays of all or part of the data packets transmitted in network slice #1 within time period #1, and determine the average value of the delays of all or part of the above data packets as the average delay.

As an example, the unit of the network energy efficiency may be 0.1 millisecond*joule (ms*J).

1.2 Network Energy Efficiency Based on Latency and Traffic

Network energy efficiency based on latency and traffic refers to the network energy efficiency determined based on the average latency and traffic of the network.

Optionally, the network energy efficiency based on latency and traffic can also determine the network energy efficiency based on the average latency of the network and the traffic of at least one interface, and the traffic of the at least one interface may include: the traffic of the N3 interface and the traffic of the N9 interface. Taking the network energy efficiency based on latency and traffic of network slice #2 (for example, URLLC network service) as an example, the network energy efficiency based on latency and traffic of network slice #2 can satisfy the following formula 4:

Wherein, EE _{URLLLC, Latency2} is the network energy efficiency based on latency and traffic of network slice #2 in time period #2. Network slice mean latency2 is the average latency of network slice #2 in time period #2. _{EC URLLLC, Latency2} is the energy consumption of network slice #2 in time period #2. w _N3 is the weight corresponding to the traffic of N3 interface. DV _N3 is the traffic of N3 interface of network slice #2 in time period #2. w _N9 is the weight corresponding to the traffic of N9 interface. _{DV N9} is the traffic of N9 interface of network slice #2 in time period #2.

From the above formula 4, it can be seen that P _{URLLLC,Latency2} satisfies the following formula 5:

Optionally, the above Network slice mean latency2 may satisfy the following formula 6:
Network slice mean latency2＝DelayE2EULNs2+DelayE2EDLNs2 Formula 6

Wherein, DelayE2EULNs2 is the average uplink delay of network slice #2 in time period #2. DelayE2EDLNs2 is the average downlink delay of network slice #2 in time period #2.

It should be pointed out that since the average latency and/or traffic of the network slice is different during busy hours and off-peak hours, the network energy efficiency based on latency and traffic of the network slice is also different during busy hours and off-peak hours. This makes the above-mentioned network energy efficiency based on latency and traffic applicable to scenarios for determining the network energy efficiency of network slices in different time periods.

3. Reliability

Reliability is an important indicator for communication network planning, design and performance evaluation. It can be used to characterize the degree to which the network can correctly implement its functions according to user requirements and design goals.

In a possible implementation, the reliability may include the following four reliabilities: Uu port downlink transmission reliability, Uu port uplink transmission reliability, delay-based downlink reliability, and delay-based uplink reliability. Different reliabilities are described below.

2.1. Uu port downlink transmission reliability

The Uu port downlink transmission reliability refers to the ratio of the number of successfully transmitted downlink data packets to the total number of downlink data packets based on the interface between the access network device and the terminal device (for example, the Uu interface). It can be used to evaluate the impact of the downlink transmission reliability of the Uu interface on the reliability of the entire network.

In a possible implementation, the Uu port downlink transmission reliability may satisfy the following formula 7:

Where DLRelPSR_Uu is the downlink transmission reliability of the Uu port in time period #3. N(T1,drbid) is the number of data packets successfully transmitted in time period #3 based on the interface between the access network device and the terminal device. Dloss(T1,drbid) is the number of data packets that failed to be transmitted in time period #3 based on the interface between the access network device and the terminal device.

In an optional implementation, the above data packet may be a service data unit (SDU) data packet with a data radio bearer (DRB) identifier and may be carried on a radio link layer control protocol (RLC) of a data radio. In this case, "N(T1,drbid)" is the number of data packets that have been transmitted over-the-air and received a positive response in time period #3 based on the Uu interface. "Dloss(T1,drbid)" is the number of data packets that have been transmitted over-the-air in time period #3 based on the Uu interface but have not received a positive response and will not be transmitted again in transmission time period #1.

Optionally, if data packet #1 has been transmitted over the air in time period #3 but has not received a positive response, but is transmitted again by the cell or by another cell in transmission time period #1, then the data packet #1 is Packet #1 cannot be counted as a data packet in the above "Dloss(T1,drbid)" statistics.

It should be pointed out that the above-mentioned Uu port downlink transmission reliability can be counted based on the granularity of network slices, the granularity of cells, and the granularity of service quality (QoS) level.

2.2 Uu port uplink data transmission reliability

The Uu port uplink transmission reliability refers to the ratio of the number of successfully transmitted uplink data packets to the total number of uplink data packets based on the interface between the terminal device and the access network device (for example, the Uu interface). It can be used to evaluate the impact of the Uu interface's uplink transmission reliability on the reliability of the entire network.

In a possible implementation, the Uu port downlink transmission reliability may satisfy the following formula 8:

Among them, ULRelPSR_Uu is the downlink transmission reliability of the Uu port in time period #4. A1 is the number of data packets successfully transmitted in time period #4 based on the interface between the access network device and the terminal device. A2 is the number of data packets that failed to be transmitted in time period #4 based on the interface between the access network device and the terminal device.

In an optional implementation, the above data packets may be packet data convergence protocol (PDC) SDU data packets. In this case, A1 is the number of uplink (UL) PDCP sequence numbers successfully received over the Uu interface in time period #4. A2 is the number of all UL PDCP sequence numbers transmitted over the Uu interface in time period #4 (i.e., including the sequence numbers from the first PDCP SDU data packet to the last PDCP SDU data packet transmitted over the Uu interface in time period #4).

It should be pointed out that the above-mentioned Uu port uplink transmission reliability can be counted at the granularity of network slices, at the granularity of cells, at the granularity of QoS levels, at the granularity of the fifth generation service quality identifier (5G quality of service identifier, 5QI), and at the granularity of QoS class identifier (QoS class identifier, QCI) level.

2.3 Uplink reliability based on latency

The delay-based uplink reliability refers to the ratio of the number of uplink data packets that are successfully transmitted in time period #5 and whose transmission time is less than or equal to that in time period #1 to the total number of uplink data packets, that is, the ratio of the number of uplink data packets that are successfully transmitted in time period #5 and whose transmission time is less than or equal to that in time period #1 to the total number of uplink data packets transmitted in time period #5.

Optionally, the transmission time period #1 can be set according to actual conditions. For example, the transmission time period #1 mentioned above is 5 milliseconds (ms).

2.4 Downlink reliability based on latency

The delay-based uplink reliability refers to the ratio of the number of uplink data packets that are successfully transmitted in time period #6 and whose transmission time is less than or equal to that in transmission time period #2 to the total number of uplink data packets, that is, the ratio of the number of uplink data packets that are successfully transmitted in time period #6 and whose transmission time is less than or equal to that in transmission time period #2 to the total number of uplink data packets transmitted in time period #6.

Optionally, the transmission time period #2 may be the same as the transmission time period #1, for example, both the transmission time period #1 and the transmission time period #2 are 5ms; the transmission time period #2 may be different from the transmission time period #1, for example, both the transmission time period #1 and the transmission time period #2 are 6ms.

The above is a brief introduction to some concepts involved in the embodiments of this application.

As shown in FIG1 , FIG1 shows a schematic diagram of the structure of a communication system provided in an embodiment of the present application. The communication system 10 includes: a computing device 101 , an access network device 102 , and a terminal device 103 .

The computing device 101 may be a physical server of a communication operator, or a virtual server of a communication operator, such as a cloud server.

The access network device 102 is located at the access network side of the communication system 10 and has a wireless transceiver function or a chip or chip system that can be set in the device.

In some examples, the access network device 102 includes, but is not limited to: an access point (AP) in a WiFi system, such as a home gateway, a router, a server, a switch, a bridge, etc., an evolved NodeB (eNB), a radio network controller (RNC), a NodeB (NB), a base station controller (BSC), a base transceiver station (BTS), a home base station (e.g., home evolved NodeB, or home NodeB, HNB), a base band unit (BBU), a wireless relay node, a wireless backhaul node, a transmission point (TRP or TP), etc., and can also be a 5G base station, such as a gNB in a new radio (NR) system, or a transmission point (TRP or TP), one or a group of (including multiple antenna panels) antenna panels of a base station in a 5G system, or a network node constituting a gNB or a transmission point, such as a baseband unit (BBU), or a distributed unit (DU), a roadside unit (roadside unit) with base station functions. The access network equipment 102 also includes base stations in different networking modes, such as a master evolved NodeB (MeNB), an auxiliary base station, and a 5G side unit (RSU). The access network equipment 102 also includes different types, such as ground base stations, air base stations, and satellite base stations.

The terminal device 103 is a device with wireless communication function, which can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted, or on water (such as ships, etc.) or in the air (such as airplanes, balloons, satellites, etc.).

In some examples, the terminal device 103 is also referred to as user equipment (UE), mobile station (MS), mobile terminal (MT), terminal, etc., and is a device that provides voice and/or data connectivity to users. For example, the terminal device 103 includes a handheld device with wireless connection function, a vehicle-mounted device, etc. At present, the terminal device 103 can be: a mobile phone, a tablet computer, a laptop computer, a PDA, a mobile internet device (MID), a wearable device (such as a smart watch, a smart bracelet, a pedometer, etc.), a vehicle-mounted device (such as a car, a bicycle, an electric car, an airplane, a ship, a train, a high-speed train, etc.), a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a smart home device (such as a refrigerator, a television, an air conditioner, an electric meter, etc.), an intelligent robot, a workshop equipment, a wireless terminal in self-driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, or a wireless terminal in a smart home, a flying device (such as an intelligent robot, a hot air balloon, a drone, an airplane), etc. In one possible application scenario of the present application, the terminal device is a terminal device that often works on the ground, such as a vehicle-mounted device. In the present application, for the convenience of description, the chip deployed in the above-mentioned device, such as a system-on-a-chip (SOC), a baseband chip, etc., or other chips with communication functions can also be referred to as a terminal device 103.

Optionally, the terminal device 103 may be an embedded communication device or a user's handheld communication device, including a mobile phone, a tablet computer, etc.

As an example, in the embodiment of the present application, the terminal device 103 can also be a wearable device. Wearable devices can also be called wearable smart devices, which are a general term for wearable devices that use wearable technology to intelligently design and develop wearable devices for daily wear, such as glasses, gloves, watches, clothing and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also realize powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable devices are Smart devices include those that are fully functional, large in size, and can achieve full or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

It should be noted that Figure 1 is only an exemplary framework diagram. The number of nodes included in Figure 1 is not limited, and in addition to the functional nodes shown in Figure 1, other nodes may also be included, such as: core network equipment, etc. This application does not impose any restrictions on this.

The core network equipment may include at least one of the following network element function entities: authentication management function (AMF), session management function (SMF), user plane function (UPF), authentication service function (AUSF), network slice selection function (NSSF), network exposure function (NEF), policy control function (PCF), unified data management function (UDM), terminal control element (TCE), master communication equipment (MCE), and operation administration and maintenance (OAM) equipment.

Among them, the specific functions of the above network element functional entities are as follows: AMF is responsible for user access and mobility management; SMF is responsible for user session management; AUSF is responsible for authenticating users' 3GPP and non-3GPP access; UPF is responsible for user plane processing; NSSF is responsible for selecting network slices used by user services; NEF is responsible for opening the capabilities of 5G networks to external systems; PCF is responsible for user policy control, including session policies, mobility policies, etc.; UDM is responsible for user contract data management. OAM equipment refers to functional network elements that operate, manage, and maintain communication networks according to the actual needs of operator network operations. Among them, operation mainly refers to the analysis, prediction, planning, and configuration of communication networks and services in communications. Management mainly refers to the management and monitoring of data in communication networks. Maintenance mainly refers to testing and fault management of communication networks and services in communication networks.

The computing device 101 is used to determine first data of a target slice within a target time period and reliability of the target slice within the target time period, and determine energy efficiency of the target slice within the target time period based on the first data and reliability.

The first data includes: at least one of energy consumption, average delay and flow; reliability is used to characterize the data packets transmitted between the target access network device 102 and the target terminal device 103. The target access network device and the target terminal device are both devices in the target slice.

Data packets can be transmitted between the target access network device 102 and the target terminal device 103 .

The communication system 10 provided in the embodiment of the present application can be various communication systems, such as: code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal frequency-division multiple access (OFDMA), single carrier frequency division multiple access (SC-FDMA) and other systems. The term "system" can be interchangeable with "network". The CDMA system can implement wireless technologies such as universal terrestrial radio access (UTRA) and CDMA2000. UTRA can include wideband CDMA (WCDMA) technology and other CDMA variant technologies. CDMA2000 can cover interim standard (IS) 2000 (IS-2000), IS-95 and IS-856 standards. The TDMA system can implement wireless technologies such as the global system for mobile communications (GSM). The OFDMA system can implement wireless technologies such as evolved UTRA (E-UTRA), ultra mobile broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, Flash OFDMA, etc. UTRA and E-UTRA are UMTS and UMTS evolution versions. 3GPP's long term evolution (LTE) and various versions based on LTE evolution are new versions of UMTS using E-UTRA. 5G communication system and NR are communication systems under study. In addition, the communication system can also be applied to future-oriented communication technologies, and the technical solutions provided in the embodiments of the present application are applicable.

In addition, the communication system described in the embodiment of the present application is intended to more clearly illustrate the technical solution of the embodiment of the present application, and does not constitute a limitation on the technical solution provided in the embodiment of the present application. A person of ordinary skill in the art can know that with the evolution of network architecture and the emergence of new communication systems, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.

In communication networks, network energy efficiency can affect operators' decisions in multiple stages (e.g., purchasing stage, design/construction stage, operation stage, etc.). As mentioned above, network energy efficiency plays a key role in operators obtaining the actual network conditions at different stages.

During the purchasing phase, operators can compare the energy efficiency of equipment from different suppliers based on network energy efficiency, and then select network equipment with higher network energy efficiency.

During the design/construction phase, operators can use network energy efficiency as a reference factor in designing networks (or sub-networks, or network sites), and can also determine whether to build a network based on network energy efficiency. A network (or subnetwork, or network site).

During the operation phase, the operator may evaluate the network energy efficiency of the network (or sub-network, or network site), and determine subsequent network decisions regarding the network energy efficiency based on the network energy efficiency.

At present, the determination of network energy efficiency is mainly based on indicators such as energy consumption, latency, and traffic. However, the above indicators cannot fully reflect the actual situation of the network, which in turn leads to the above indicators being unable to fully reflect the actual situation of the network. This will result in the determined network energy efficiency being unable to reflect the actual situation of the network well, resulting in operators being unable to make correct decisions based on the above network energy efficiency.

In order to solve the problems existing in the above-mentioned prior art, the embodiment of the present application proposes a method for determining network energy efficiency, which can improve the accuracy of network energy efficiency. As shown in Figure 2, the method includes:

S201. A computing device determines first data of a target slice within a target time period, and reliability of the target slice within the target time period.

The first data includes at least one of energy consumption, average delay and flow. Reliability is used to characterize the transmission success rate of data packets transmitted between the target access network device and the target terminal device. The target access network device and the target terminal device are both devices in the target slice.

In one example, the target access network device and the target terminal device may transmit data packets via a Uu interface. The target access network device and the target terminal device may also transmit data packets via other interfaces, which is not limited in this application.

In a possible implementation, the above average delay may be the average delay of all or part of the data packets transmitted by the target slice within the target time period. The above traffic may include: the uplink traffic of the target slice within the target time period, and the downlink traffic of the target slice within the target time period. The above energy consumption may be the energy consumption of the access network device and/or core network device and/or terminal device in the target slice within the target time period.

Optionally, the computing device can set the target time period according to actual conditions. For example, the computing device sets the target time period to 30 minutes. The computing device can also set the target time period to other time periods (for example, 3 hours). This application does not impose any restrictions on this.

Optionally, the above-mentioned first data may also include other data, and this application does not impose any limitation on this.

S202. The computing device determines the network energy efficiency of the target slice within the target time period based on the first data and reliability.

As an optional implementation method, the implementation process of the above S202 may be: the computing device The performance of the network slice of the target slice within the target time period can be determined based on reliability and average delay, or reliability, average delay, and traffic, and the ratio of the performance of the above network slice to the energy consumption in the first data is determined as the network energy efficiency of the target slice within the target time period.

As another optional implementation method, the implementation process of the above S202 can be: the computing device can first determine the network energy efficiency of the target slice within the target time period based on reliability, energy consumption, and average delay, or reliability, energy consumption, average delay, and traffic.

Optionally, the method shown in Figure 2 above is applicable to determining the network energy efficiency of the slice. The network energy efficiency determination method provided in this application can also be applied to determine the network energy efficiency of the cell, the network energy efficiency of the public land mobile network (PLMN), and the network energy efficiency of 5QI, etc. This application does not impose any restrictions on this. The implementation process of the computing device determining the network energy efficiency of the cell, the network energy efficiency of the PLMN, and the network energy efficiency of 5QI can be understood by referring to the description of S201 to S202 above, which will not be repeated here.

The above technical solution brings at least the following beneficial effects: the network energy efficiency determination method provided by the present application, the computing device can determine the first data (i.e. at least one of energy consumption, average delay and flow) and reliability of the target slice within the target time period, and determine the network energy efficiency of the target slice within the target time period based on the above-determined first data and reliability. Therefore, the network energy efficiency determination method provided by the present application can combine indicators such as energy consumption, delay, and flow with reliability, and together serve as data support for determining network energy efficiency, so that the determination of network energy efficiency can more comprehensively and accurately reflect the actual situation of the network, thereby improving the accuracy of network energy efficiency.

In an optional embodiment, as shown in S201, the computing device needs to first determine the reliability of the target slice within the target time period, so as to determine the network energy efficiency improvement data support for the subsequent computing device. Therefore, this embodiment provides a possible implementation method based on the method embodiment shown in FIG2. As shown in FIG3, the implementation process of the computing device determining the reliability of the target slice within the target time period can be determined by the following S301 to S302.

S301. The computing device obtains the first number of data packets, and any one of the second number of data packets and the third number of data packets of the target slice within the target time period.

The first data packet is used to characterize the data packet transmitted based on the target interface. The second data packet is used to characterize the data packet successfully transmitted based on the target interface. The number of third data packets is used to characterize the number of data packets in the second data packet whose delay is less than or equal to the preset time period. The target interface is the interface between the target access network device and the target terminal device.

In a possible implementation, the number of first data packets includes: the number of uplink first data packets and the number of downlink first data packets. The uplink first data packets are data packets sent by the target terminal device. The downlink first data packets are data packets sent by the access network device. The number of second data packets includes: the number of uplink second data packets and the number of downlink second data packets. The uplink second data packets are data packets received by the target terminal device. The downlink second data packets are data packets received by the target access network device. The number of third data packets includes: the number of uplink third data packets and the number of downlink third data packets. The uplink third data packets are data packets in the uplink second data packets whose delay is less than or equal to the first preset time period. The number of downlink third data packets is data packets in the downlink second data packets whose delay is less than or equal to the second preset time period.

Optionally, the computing device may set the first preset time period and the second preset time period to the same time period, for example, the computing device sets both the first preset time period and the second preset time period to 10 ms. The computing device may also set the first preset time period and the second preset time period to different time periods, for example, the computing device sets the first preset time period to 5 ms and the second preset time period to 6 ms.

It should be noted that the computing device can set a preset time period according to actual conditions, and this application does not impose any restrictions on this.

S302. The computing device determines the reliability of the target slice within the target time period based on the number of the first data packets and any one of the number of the second data packets and the number of the third data packets.

Optionally, the computing device may determine the reliability of the target slice within the target time period in four implementation methods. The six implementation methods are described below respectively.

In implementation 1, the reliability satisfies the following formula 9:
Re＝(DLA2/DLA1)×(ULA2/ULA1) Formula 9

Wherein, Re is reliability. DLA1 is the number of downlink first data packets. DLA2 is the number of downlink second data packets. ULA1 is the number of uplink first data packets. ULA2 is the number of uplink second data packets.

As an example, taking the number of downlink first data packets (i.e., DLA1) as 100, the number of downlink second data packets (DLA2) as 80, the number of uplink first data packets (ULA1) as 80, and the number of uplink second data packets (ULA2) as 80, the computing device can determine that the reliability in implementation method 1 is 80% (i.e., (80/100)×(80/80)).

In another example, the number of downlink first data packets (ie, DLA1) is 100, the number of downlink second data packets (DLA2) is 90, the number of uplink first data packets (ULA1) is 90, and the number of uplink second data packets (ULA2) is 90. The computing device may determine that in implementing The reliability in mode 1 is 90% (ie, (90/100)×(90/90)).

In implementation 2, the reliability satisfies the following formula 10:
Re＝(DLA2+ULA2)/(DLA1+ULA1) Formula 10

As an example, taking the number of downlink first data packets (i.e., DLA1) as 100, the number of downlink second data packets (DLA2) as 80, the number of uplink first data packets (ULA1) as 80, and the number of uplink second data packets (ULA2) as 80, the computing device can determine that the reliability in implementation method 1 is 88.9% (i.e., (80+80)/(100+80)).

As another example, taking the number of downlink first data packets (i.e., DLA1) as 100, the number of downlink second data packets (DLA2) as 90, the number of uplink first data packets (ULA1) as 90, and the number of uplink second data packets (ULA2) as 90, the computing device can determine that the reliability in implementation method 1 is 94.7% (i.e., (90+90)/(100+90)).

In implementation 3, the reliability satisfies the following formula 11:
Re＝(DLA3/DLA1)×(ULA3/ULA1) Formula 11

As an example, taking the number of downlink first data packets (i.e., DLA1) as 100, the number of downlink third data packets (DLA2) as 70, the number of uplink first data packets (ULA1) as 70, and the number of uplink third data packets (ULA2) as 60, the computing device can determine that the reliability in implementation method 3 is 60% (i.e., (70/100)×(60/70)).

As another example, taking the number of downlink first data packets (i.e., DLA1) as 100, the number of downlink third data packets (DLA2) as 80, the number of uplink first data packets (ULA1) as 80, and the number of uplink third data packets (ULA2) as 60, the computing device can determine that the reliability in implementation method 3 is 60% (i.e., (80/100)×(60/80)).

In implementation mode 4, the reliability satisfies the following formula 12:
Re＝(DLA3+ULA3)/(DLA1+ULA1) Formula 12

As an example, taking the number of downlink first data packets (i.e., DLA1) as 100, the number of downlink third data packets (DLA2) as 70, the number of uplink first data packets (ULA1) as 70, and the number of uplink third data packets (ULA2) as 60, the computing device can determine that the reliability in implementation method 3 is 76.5% (i.e., (70+60)/(100+70)).

As another example, taking the number of downlink first data packets (i.e., DLA1) as 100, the number of downlink third data packets (DLA2) as 80, the number of uplink first data packets (ULA1) as 80, and the number of uplink third data packets (ULA2) as 60, the computing device can determine that the reliability in implementation method 3 is 77.8% (i.e., (80+60)/(100+80)).

Optionally, the above is only an exemplary description of the computing device determining reliability. The computing device may also The reliability of the target slice within the target time period may be determined by other means, and this application does not impose any limitation on this.

The above technical solution brings at least the following beneficial effects: In the network energy efficiency method provided by the present application, the computing device can obtain any one of the number of first data packets (i.e., the total number of data packets transmitted) of the target slice within the target time period, the number of second data packets (i.e., the number of data packets successfully transmitted), and the number of third data packets (i.e., the number of data packets in the above second data packets whose delay is less than or equal to the preset time period), and determine the reliability based on the number of the above first data packets, and any one of the number of second data packets and the number of third data packets, thereby providing data support for subsequent computing devices to determine the network energy efficiency based on reliability.

In some optional embodiments, the first data can be divided into the following four cases: Case 1, the first data includes energy consumption. Case 2, the first data includes energy consumption and average delay. Case 3, the first data includes energy consumption and traffic, and the traffic includes: uplink traffic and downlink traffic. Case 4, the first data includes energy consumption, average delay, and traffic, and the traffic includes: uplink traffic and downlink traffic. In different cases, the implementation process of the computing device determining the network energy efficiency is different, so the implementation process of the computing device determining the network energy efficiency in the above four cases is described separately below.

Case 1: The first data includes energy consumption.

In case 1, in combination with FIG. 3 , as shown in FIG. 4 , the implementation process of the computing device determining the network energy efficiency may be implemented through the following S401 .

S401. The computing device determines that the ratio of reliability to energy consumption is the network energy efficiency.

As a possible implementation method, the implementation process of the above S301 can be: the computing device can first determine the reliability as the performance of the network slice (ie, Pns), and then determine the ratio of the target value to the energy consumption as the network energy efficiency.

For example, taking reliability #1 as 47.4%, reliability #2 as 66.7%, reliability #3 as 81%, reliability #4 as 66.7%, reliability #4 as 47.4%, and energy consumption as 5J as an example, the computing device can determine that the network energy efficiency is 0.095 based on reliability #1, 0.13 based on reliability #2, 0.16 based on reliability #3, and 0.13 based on reliability #4.

Case 2: The first data includes energy consumption and average delay.

In case 2, in combination with FIG. 3 , as shown in FIG. 4 , the implementation process of the computing device determining the network energy efficiency may be implemented through the following S402 to S403 .

S402: The computing device determines that the ratio of reliability to average delay is a first value.

For example, reliability #1 is 47.4%, reliability #2 is 66.7%, and reliability #3 is Taking the average delay as 10ms as an example, the computing device can determine a first value based on reliability #1 (recorded as first value #11) of 4.74%, a first value based on reliability #2 (recorded as first value #12) of 6.67%, a first value based on reliability #3 (recorded as first value #13) of 8.1%, and a first value based on reliability #4 (recorded as first value #14) of 6.67%.

As another example, taking reliability #1 as 47.4%, reliability #2 as 66.7%, reliability #3 as 81%, reliability #4 as 66.7%, and average delay as 1 ms, the computing device may determine a first value (recorded as first value #21) of 47.4% based on reliability #1, a first value (recorded as first value #22) of 66.7% based on reliability #2, a first value (recorded as first value #23) of 81% based on reliability #3, and a first value (recorded as first value #24) of 66.7% based on reliability #4.

In this case, the first value can be used as the performance of the network slice (i.e., Pns).

S403: The computing device determines that the ratio of the first value to the energy consumption is the network energy efficiency.

In one example, taking the first value #11 as 4.74%, the first value #12 as 6.67%, the first value #13 as 8.1%, the first value #14 as 6.67%, and the energy consumption as 5J, the computing device can determine that the network energy efficiency is 0.01356 based on the first value #11, the network energy efficiency is 0.013 based on the first value #12, the network energy efficiency is 0.016 based on the first value #13, and the network energy efficiency is 0.013 based on the first value #14.

As another example, taking the first value #21 as 47.4%, the first value #22 as 66.7%, the first value #23 as 81%, the first value #24 as 66.7%, and the energy consumption as 10J, the computing device can determine that the network energy efficiency is 0.0474 based on the first value #21, the network energy efficiency is 0.0667 based on the first value #22, the network energy efficiency is 0.081 based on the first value #23, and the network energy efficiency is 0.0667 based on the first value #24.

Case 3: The first data includes energy consumption and flow rate.

In case 3, in combination with FIG. 3 , as shown in FIG. 4 , the implementation process of the computing device determining the network energy efficiency may be implemented through the following S404 to S405 .

S404: The computing device performs a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determines that the product of the reliability and the second value is a third value.

As an optional implementation method, the implementation process of the computing device determining the second value can be: the computing device first determines the product of the weight corresponding to the uplink traffic and the uplink traffic, and the product of the weight corresponding to the downlink traffic and the downlink traffic, and then adds the above products to obtain the second value.

In an example (referred to as Example 1), the upstream flow is 1000 bits. For example, if the weight corresponding to the amount is 0.9, the downlink traffic is 100 bits, and the weight corresponding to the downlink traffic is 0.1, the computing device can determine that the second value is 910 (ie, 0.9×1000+0.1×100) bits.

In combination with the above examples, taking reliability #1 as 47.4%, reliability #2 as 66.7%, reliability #3 as 81%, reliability #4 as 66.7%, and the second value as 910 bits, the computing device can determine the third value (recorded as third value #1) as 431.34 based on reliability #1 and the second value, determine the third value (recorded as third value #2) as 606.97 based on reliability #2 and the second value, determine the third value (recorded as third value #3) as 737.1 based on reliability #3 and the second value, and determine the third value (recorded as third value #4) as 606.97 based on reliability #4 and the second value.

In this case, the third value can be used as the performance of the network slice (i.e., Pns).

Exemplarily, the first interface may be an N3 interface, and the second interface may be an N9 interface.

S405. The computing device determines that the ratio of the third value to the energy consumption is the network energy efficiency.

For example, taking the third value #1 as 431.34, the third value #2 as 606.97, the third value #3 as 737.1, the third value #4 as 606.97, and the energy consumption as 5J, the computing device can determine that the network energy efficiency is 86.45 based on the third value #1 and the energy consumption, determine that the network energy efficiency is 121.4 based on the third value #2 and the energy consumption, determine that the network energy efficiency is 147.4 based on the third value #3 and the energy consumption, and determine that the network energy efficiency is 121.4 based on the third value #4 and the energy consumption.

Case 4: The first data includes energy consumption, average delay, and traffic.

In case 4, in combination with FIG. 3 , as shown in FIG. 4 , the implementation process of the computing device determining the network energy efficiency may be implemented through the following S406 to S407 .

S406. The computing device performs a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determines a ratio of the product of the reliability and the second value to the average delay as a fourth value.

In a possible implementation, the uplink traffic may be the amount of data sent by the target terminal device to the target access network device, and the downlink traffic may be the amount of data sent by the target terminal device to the target access network device.

In another example (referred to as Example 2), taking the uplink traffic as 10,000 bits and the corresponding weight of the uplink traffic as 0.9, and the downlink traffic as 1,000 bits and the corresponding weight of the downlink traffic as 0.1, the computing device can determine that the second value is 9,100 (i.e., 0.9×1000+0.1×100) bits.

In combination with the above example 1, taking reliability #1 as 47.4%, reliability #2 as 66.7%, reliability #3 as 81%, reliability #4 as 66.7%, the second value as 910 bits, and the average delay as 10 ms as an example, the computing device can determine the fourth value (recorded as the fourth value #11) as 43.134 based on reliability #1, the second value, and the average delay, and determine the fourth value (recorded as the fourth value #11) as 43.134 based on reliability #2 and the second value. The fourth value #12) is 60.697, the fourth value (recorded as the fourth value #13) is 73.71 based on reliability #3, the second value, and the average delay, and the fourth value (recorded as the fourth value #14) is 60.697 based on reliability #4, the second value, and the average delay.

In combination with the above Example 2, taking reliability #1 as 47.4%, reliability #2 as 66.7%, reliability #3 as 81%, reliability #4 as 66.7%, the second value as 9100 bits, and the average delay as 10 ms as an example, the computing device can determine the fourth value (recorded as fourth value #21) as 431.34 based on reliability #1, the second value, and the average delay, determine the fourth value (recorded as fourth value #22) as 606.97 based on reliability #2 and the second value, determine the fourth value (recorded as fourth value #23) as 737.1 based on reliability #3, the second value, and the average delay, and determine the fourth value (recorded as fourth value #24) as 606.97 based on reliability #4, the second value, and the average delay.

In this case, the fourth value can be used as the performance of the network slice (i.e., Pns).

S407: The computing device determines that the ratio of the fourth value to the energy consumption is the network energy efficiency.

In one example, taking the fourth value #11 as 43.134, the fourth value #12 as 60.697, the fourth value #13 as 73.71, the fourth value #14 as 60.697, the fourth value #15 as 61.698, the fourth value #16 as 43.134, and the energy consumption as 5J, the computing device can determine that the network energy efficiency is 8.645 based on the fourth value #11 and the energy consumption, determine that the network energy efficiency is 12.14 based on the fourth value #12 and the energy consumption, determine that the network energy efficiency is 14.74 based on the fourth value #13 and the energy consumption, and determine that the network energy efficiency is 12.14 based on the fourth value #14 and the energy consumption.

As another example, taking the fourth value #21 as 431.34, the fourth value #22 as 606.97, the fourth value #23 as 737.1, the fourth value #24 as 606.97, and the energy consumption as 5J, the computing device can determine that the network energy efficiency is 86.45 based on the fourth value #21 and the energy consumption, determine that the network energy efficiency is 121.4 based on the fourth value #22 and the energy consumption, determine that the network energy efficiency is 147.4 based on the fourth value #23 and the energy consumption, and determine that the network energy efficiency is 121.4 based on the fourth value #24 and the energy consumption.

In an optional implementation, the traffic may also include traffic of the first interface and traffic of the second interface. Exemplarily, the first interface may be an N3 interface, and the second interface may be a Uu interface. When the traffic includes traffic of the first interface and traffic of the second interface, the implementation process of the computing device determining the network energy efficiency may be understood by referring to S404 to S407 above, and will not be described in detail here.

The above technical solution brings at least the following beneficial effects: the network energy efficiency determination method provided in the present application, the computing device can determine the network energy consumption based on energy consumption, average delay, and reliability, or energy consumption, average delay, traffic, and reliability, thus providing multiple implementation methods for determining energy consumption to better adapt to different situations.

It is understandable that the above network energy efficiency determination method can be implemented by a network energy efficiency determination device. Now. In order to realize the above functions, the network energy efficiency determination device includes hardware structures and/or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the modules and algorithm steps of each example described in the embodiments disclosed herein, the embodiments disclosed in this application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the embodiments disclosed in this application.

The embodiments disclosed in the present application can divide the functional modules of the network energy efficiency determination device generated by the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiments disclosed in the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

Fig. 5 is a schematic diagram of the structure of a network energy efficiency determination device provided by an embodiment of the present invention. As shown in Fig. 5, the network energy efficiency determination device 50 can be used to execute the network energy efficiency determination method shown in Fig. 2 to Fig. 4. The network energy efficiency determination device 50 includes: a processing unit 501.

Processing unit 501 is used to determine the first data of the target slice within the target time period, and the reliability of the target slice within the target time period; the first data includes: at least one of energy consumption, average delay and traffic; reliability is used to characterize the transmission success rate of data packets transmitted between the target access network device and the target terminal device; the target access network device and the target terminal device are both devices in the target slice; processing unit 501 is also used to determine the network energy efficiency of the target slice within the target time period based on the first data and reliability.

In a possible implementation, the network energy efficiency determination device also includes: a communication unit 502; the communication unit 502 is also used to obtain the number of first data packets of the target slice within the target time period, and any one of the number of second data packets and the number of third data packets; the first data packet is used to characterize the data packet transmitted based on the target interface; the second data packet is used to characterize the data packet successfully transmitted based on the target interface; the number of third data packets is used to characterize the number of data packets in the second data packet whose delay is less than or equal to the preset time period; the target interface is the interface between the target access network device and the target terminal device; the processing unit 501 is also used to determine the reliability of the target slice within the target time period based on the number of first data packets, and any one of the number of second data packets and the number of third data packets.

In a possible implementation manner, when the first data includes energy consumption, the processing unit 501 is further configured to determine a ratio of reliability to energy consumption as network energy efficiency.

In a possible implementation, when the first data includes energy consumption and average delay The processing unit 501 is further used to determine that the ratio of reliability to average delay is a first value; the processing unit 501 is further used to determine that the ratio of the first value to energy consumption is network energy efficiency.

In one possible implementation, when the first data includes energy consumption and traffic, and the traffic includes: uplink traffic and downlink traffic, the processing unit 501 is also used to perform a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determine the product of the reliability and the second value as a third value; the processing unit 501 is also used to determine the ratio of the third value to the energy consumption as the network energy efficiency.

In a possible implementation, when the first data includes energy consumption, average delay, and traffic, and the traffic includes: uplink traffic and downlink traffic, the processing unit 501 is also used to perform a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determine the product of the reliability and the second value, and the ratio of the product to the average delay is a fourth value; the processing unit 501 is also used to determine the ratio of the fourth value to the energy consumption as the network energy efficiency.

In the case of implementing the functions of the above-mentioned integrated modules in the form of hardware, an embodiment of the present invention provides a possible structural diagram of the network energy efficiency determination device involved in the above-mentioned embodiment. As shown in Figure 6, a network energy efficiency determination device 60 is used to perform the network energy efficiency determination method shown in Figures 2-4. The network energy efficiency determination device 60 includes a processor 601, a memory 602, and a bus 603. The processor 601 and the memory 602 can be connected via a bus 603. Optionally, the network energy efficiency determination device 60 may also include a communication interface 604.

The processor 601 is the control center of the user equipment, which can be a processor or a general term for multiple processing elements. For example, the processor 601 can be a general-purpose central processing unit 602 (CPU) or other general-purpose processors. Among them, the general-purpose processor can be a microprocessor or any conventional processor.

As an embodiment, processor 601 may include one or more CPUs, such as CPU 0 and CPU 1 shown in Figure 6.

The memory 602 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

As a possible implementation, the memory 602 may exist independently of the processor 601. The memory 602 can be connected to the processor 601 via the bus 603 and is used to store instructions or program codes. When the processor 601 calls and executes the instructions or program codes stored in the memory 602, the map drawing method provided by the embodiment of the present invention can be implemented.

In another possible implementation, the memory 602 may also be integrated with the processor 601 .

The bus 603 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, FIG6 only uses one thick line, but does not mean that there is only one bus or one type of bus.

The communication interface 604 is used to connect with other devices through a communication network. The communication network can be Ethernet, wireless access network, wireless local area network (WLAN), etc. The communication interface 604 may include a communication unit 501 for receiving data.

In one design, in the network energy efficiency determination device 60 provided in an embodiment of the present invention, the communication interface may also be integrated into a processor.

It should be noted that the structure shown in Fig. 6 does not limit the network energy efficiency determination device 60. In addition to the components shown in Fig. 6, the network energy efficiency determination device 60 may include more or fewer components than shown, or combine certain components, or arrange the components differently.

As an example, in combination with FIG. 5 , the function implemented by the processing unit 501 in the network energy efficiency determination device is the same as the function of the processor 601 in FIG. 6 .

Through the description of the above implementation methods, technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

An embodiment of the present application provides a communication system, which may include a computing device, an access network device, and a terminal device. The computing device is used to determine first data of a target slice within a target time period, and the reliability of the target slice within the target time period (i.e., a transmission success rate for characterizing data packets transmitted between the access network device and the terminal device), and determine the energy efficiency of the target slice within the target time period based on the first data and the reliability, so as to perform the present application. Please refer to the relevant descriptions in the above method embodiment and device embodiment for the description of the computing device, access network device, and terminal device, which will not be repeated here.

An embodiment of the present application provides a computer program product comprising instructions. When the computer program product is run on a computer, the computer is enabled to execute the network energy efficiency determination method described in the above method embodiment.

An embodiment of the present application also provides a computer-readable storage medium, in which instructions are stored. When a computing device executes the instructions, the computing device executes each step performed by the computing device in the method flow shown in the above method embodiment.

Among them, the computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above, or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (ASIC). In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

A method for determining network energy efficiency, characterized by comprising:

Determine first data of a target slice within a target time period, and reliability of the target slice within the target time period; the first data includes: at least one of energy consumption, average delay and flow; the reliability is used to characterize the transmission success rate of data packets transmitted between a target access network device and a target terminal device; the target access network device and the target terminal device are both devices in the target slice;

Based on the first data and the reliability, determine the network energy efficiency of the target slice within the target time period.
The method according to claim 1, characterized in that determining the reliability of the target slice within the target time period comprises:

Obtain the number of first data packets of the target slice within the target time period, and any one of the number of second data packets and the number of third data packets; the first data packet is used to characterize the data packet transmitted based on the target interface; the second data packet is used to characterize the data packet successfully transmitted based on the target interface; the number of third data packets is used to characterize the number of data packets in the second data packet whose delay is less than or equal to the preset time period; the target interface is the interface between the target access network device and the target terminal device;

The reliability of the target slice within the target time period is determined based on the number of the first data packets and any one of the number of the second data packets and the number of the third data packets.
The method according to claim 2 is characterized in that the number of the first data packets includes: the number of uplink first data packets and the number of downlink first data packets; the uplink first data packets are data packets sent by the target terminal device; the downlink first data packets are data packets sent by the access network device; the number of the second data packets includes: the number of uplink second data packets and the number of downlink second data packets; the uplink second data packets are data packets received by the target terminal device; the downlink second data packets are data packets received by the target access network device; the number of the third data packets includes: the number of uplink third data packets and the number of downlink third data packets; the uplink third data packets are data packets in the uplink second data packets whose delay is less than or equal to the first preset time period; the number of downlink third data packets is data packets in the downlink second data packets whose delay is less than or equal to the second preset time period.
The method according to claim 3, characterized in that the reliability satisfies the following formula:
Re＝(DLA2/DLA1)×(ULA2/ULA1)

Among them, the Re is the reliability; the DLA1 is the number of the downlink first data packets; the DLA2 is the number of the downlink second data packets; the ULA1 is the number of the uplink first data packets; and the ULA2 is the number of the uplink second data packets.
The method according to claim 3, characterized in that the reliability satisfies the following formula:
Re＝(DLA2+ULA2)/(DLA1+ULA1)

Among them, the Re is the reliability; the DLA1 is the number of the downlink first data packets; the DLA2 is the number of the downlink second data packets; the ULA1 is the number of the uplink first data packets; and the ULA2 is the number of the uplink second data packets.
The method according to claim 3, characterized in that the reliability satisfies the following formula:
Re＝(DLA3/DLA1)×(ULA3/ULA1)

Among them, the Re is the reliability; the DLA1 is the number of the downlink first data packets; the DLA3 is the number of the downlink third data packets; the ULA1 is the number of the uplink first data packets; and the ULA3 is the number of the uplink third data packets.
The method according to claim 3, characterized in that the reliability satisfies the following formula:
Re＝(DLA3+ULA3)/(DLA1+ULA1)

Among them, the Re is the reliability; the DLA1 is the number of the downlink first data packets; the DLA3 is the number of the downlink third data packets; the ULA1 is the number of the uplink first data packets; and the ULA3 is the number of the uplink third data packets.
The method according to any one of claims 1 to 7, characterized in that, when the first data includes the energy consumption, determining the network energy efficiency of the target slice within the target time period based on the first data and the reliability includes:

A ratio of the reliability to the energy consumption is determined as the network energy efficiency.
The method according to any one of claims 1 to 7, characterized in that, when the first data includes the energy consumption and the average delay, determining the network energy efficiency of the target slice in the target time period based on the first data and the reliability includes:

Determine a ratio of the reliability to the average delay as a first value;

A ratio of the first value to the energy consumption is determined as the network energy efficiency.
The method according to any one of claims 1 to 7 is characterized in that, when the first data includes the energy consumption and the traffic, and the traffic includes: uplink traffic and downlink traffic, determining the network energy efficiency of the target slice in the target time period based on the first data and the reliability includes:

Performing a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determining a product of the reliability and the second value as a third value;

A ratio of the third value to the energy consumption is determined as the network energy efficiency.
The method according to any one of claims 1 to 7 is characterized in that, when the first data includes the energy consumption, the average delay, and the traffic, and the traffic includes: uplink traffic and downlink traffic, determining the network energy efficiency of the target slice in the target time period based on the first data and the reliability includes:

Performing a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determining a ratio of a product of the reliability and the second value to the average delay as a fourth value;

A ratio of the fourth value to the energy consumption is determined as the network energy efficiency.
A network energy efficiency determination device, characterized in that the device comprises: a processing unit;

The processing unit is used to determine first data of a target slice within a target time period, and reliability of the target slice within the target time period; the first data includes: at least one of energy consumption, average delay and flow; the reliability is used to characterize the transmission success rate of data packets transmitted between a target access network device and a target terminal device; the target access network device and the target terminal device are both devices in the target slice;

The processing unit is further used to determine the network energy efficiency of the target slice within the target time period based on the first data and the reliability.
The device according to claim 12, characterized in that the device further comprises: a communication unit;

The communication unit is used to obtain the number of first data packets of the target slice within the target time period, and any one of the number of second data packets and the number of third data packets; the first data packet is used to characterize the data packet transmitted based on the target interface; the second data packet is used to characterize the data packet successfully transmitted based on the target interface; the number of third data packets is used to characterize the number of data packets in the second data packet whose delay is less than or equal to the preset time period; the target interface is the interface between the target access network device and the target terminal device mouth;

The processing unit is further configured to determine the reliability of the target slice within the target time period based on the number of the first data packets and any one of the number of the second data packets and the number of the third data packets.
The device according to claim 13 is characterized in that the number of first data packets includes: the number of uplink first data packets and the number of downlink first data packets; the uplink first data packets are data packets sent by the target terminal device; the downlink first data packets are data packets sent by the access network device; the number of second data packets includes: the number of uplink second data packets and the number of downlink second data packets; the uplink second data packets are data packets received by the target terminal device; the downlink second data packets are data packets received by the target access network device; the number of third data packets includes: the number of uplink third data packets and the number of downlink third data packets; the uplink third data packets are data packets in the uplink second data packets whose delay is less than or equal to the first preset time period; the number of downlink third data packets is data packets in the downlink second data packets whose delay is less than or equal to the second preset time period.
The device according to claim 14, characterized in that the reliability satisfies the following formula:
Re＝(DLA2/DLA1)×(ULA2/ULA1)

Among them, the Re is the reliability; the DLA1 is the number of the downlink first data packets; the DLA2 is the number of the downlink second data packets; the ULA1 is the number of the uplink first data packets; and the ULA2 is the number of the uplink second data packets.
The device according to claim 14, characterized in that the reliability satisfies the following formula:
Re＝(DLA2+ULA2)/(DLA1+ULA1)

Among them, the Re is the reliability; the DLA1 is the number of the downlink first data packets; the DLA2 is the number of the downlink second data packets; the ULA1 is the number of the uplink first data packets; and the ULA2 is the number of the uplink second data packets.
The device according to claim 14, characterized in that the reliability satisfies the following formula:
Re＝(DLA3/DLA1)×(ULA3/ULA1)

Wherein, Re is the reliability; DLA1 is the number of the first downlink data packets; DLA3 is the number of the third downlink data packets; ULA1 is the uplink The ULA3 is the number of the uplink third data packets.
The device according to claim 14, characterized in that the reliability satisfies the following formula:
Re＝(DLA3+ULA3)/(DLA1+ULA1)

Among them, the Re is the reliability; the DLA1 is the number of the downlink first data packets; the DLA3 is the number of the downlink third data packets; the ULA1 is the number of the uplink first data packets; and the ULA3 is the number of the uplink third data packets.
The device according to any one of claims 12 to 18, characterized in that, when the first data includes the energy consumption,

The processing unit is further used to determine a ratio of the reliability to the energy consumption as the network energy efficiency.
The device according to any one of claims 12 to 18, characterized in that, when the first data includes the energy consumption and the average delay,

The processing unit is further configured to determine that a ratio of the reliability to the average delay is a first value;

The processing unit is further configured to determine a ratio of the first value to the energy consumption as the network energy efficiency.
The device according to any one of claims 12 to 18, characterized in that, when the first data includes the energy consumption and the flow, and the flow includes: uplink flow and downlink flow,

The processing unit is further configured to perform a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determine that the product of the reliability and the second value is a third value;

The processing unit is further configured to determine a ratio of the third value to the energy consumption as the network energy efficiency.
The device according to any one of claims 12 to 18, characterized in that, when the first data includes the energy consumption, the average delay, and the flow, and the flow includes: uplink flow and downlink flow,

The processing unit is further configured to perform a weighted sum calculation on the uplink traffic and the downlink traffic to obtain a second value, and determine a ratio of a product of the reliability and the second value to the average delay as a fourth value;

The processing unit is further configured to determine a ratio of the fourth value to the energy consumption as the network energy efficiency.
A network energy efficiency determination device, characterized in that it includes: a processor and a communication interface; the communication interface is coupled to the processor, and the processor is used to run a computer program or instruction to implement the network energy efficiency determination method as described in any one of claims 1-11.
A computer-readable storage medium having instructions stored therein, characterized in that when a computer executes the instructions, the computer executes the network energy efficiency determination method described in any one of claims 1-11 above.