Communication method and apparatus

Abstract

A communication method and apparatus, relating to the technical field of communications, and used for improving the efficiency of objective optimization. The method comprises: acquiring information on an optimization area, an objective index, a weight corresponding to the objective index, and the number of strategy recommendations, wherein the information on the optimization area indicates the optimization area; and on the basis of the information on the optimization area, the weight corresponding to the objective index, and the number of strategy recommendations, sending an optimization result corresponding to the optimization area to a management service consumer, wherein the optimization result comprises at least one strategy item, the number of the at least one strategy item is equal to the number of strategy recommendations, and each strategy item among the at least one strategy item comprises a recommended value of a network parameter corresponding to the objective index and an index value corresponding to the recommended value.

Description

A communication method and apparatus

[0001] Cross-reference to Related Applications

[0002] This application claims priority to the Chinese Patent Application No. 202410670709.6, filed on May 27, 2024, and entitled "A communication method and apparatus", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0003] The present application relates to the field of communication technology, and in particular to a communication method and apparatus. BACKGROUND

[0004] When planning a wireless communication network system, a network operator adjusts network system configuration strategies in order to expect maximum optimization effect on one or more network performance indicators, so as to achieve target optimization. Taking energy saving optimization of a wireless communication network system as an example, when performing energy saving optimization on the wireless communication network system, optimization can be performed in terms of energy consumption indicators and other indicators (such as terminal experience rate), so as to achieve the lowest energy consumption within the maximum range of terminal experience rate optimization space.

[0005] For a wireless communication network system, how to improve the efficiency of target optimization is a problem to be solved at present. SUMMARY

[0006] Embodiments of the present application provide a communication method and apparatus to improve the efficiency of target optimization.

[0007] The method provided by the embodiments of the present application can be applied to a system for implementing network optimization and a functional entity included in the system. The system can include a performance analysis functional entity and an optimization functional entity. The performance analysis functional entity can be used to determine an optimization region, and the optimization functional entity can be used to determine an optimization result corresponding to the optimization region according to the optimization region. The performance analysis function and the optimization function can also be combined into a functional entity.

[0008] In a first aspect, a communication method is provided, the method comprising: obtaining information of an optimization region, a target indicator, a weight corresponding to the target indicator, and a number of strategy recommendations, the information of the optimization region indicating an optimization region; based on the information of the optimization region, the weight corresponding to the target indicator, and the number of strategy recommendations, sending an optimization result corresponding to the optimization region to a management service consumer, the optimization result including at least one strategy item, the number of the at least one strategy item being the same as the number of strategy recommendations, each of the at least one strategy item including a recommended value of a network parameter corresponding to the target indicator and an indicator value corresponding to the recommended value.

[0009] In the above implementation, on the one hand, compared with network optimization in the whole network, the optimization range can be reduced and the efficiency of target optimization can be improved by performing network optimization based on the optimization region. On the other hand, based on the weight of the target index and the number of recommended strategies, the management service consumer can be recommended with strategy items meeting the needs of the management service consumer.

[0010] Optionally, the number of recommended strategies is preset or specified by the management service consumer.

[0011] Optionally, the target index is preset or specified by the management service consumer.

[0012] Optionally, the weight corresponding to the target index is preset or specified by the management service consumer.

[0013] In a possible implementation, based on the information of the optimization region, the weight corresponding to the target index, and the number of recommended strategies, the optimization result corresponding to the optimization region is sent to the management service consumer, including: determining the evaluation value of the strategy item corresponding to each iteration round according to the weight corresponding to the target index, wherein the evaluation value of the strategy item corresponding to any iteration round is obtained according to the weighted sum value of the index value of the target index in the strategy item corresponding to the any iteration round; selecting the same number of strategy items as the number of recommended strategies from the strategy items corresponding to all iteration rounds according to the evaluation value of the strategy items corresponding to all iteration rounds; and sending the optimization result corresponding to the optimization region to the management service consumer, wherein the optimization result includes the same number of strategy items as the number of recommended strategies selected from the strategy items corresponding to all iteration rounds.

[0014] In the above implementation, based on the weight corresponding to the target index, the network performance improvement effect corresponding to different target indexes can be considered comprehensively, so that the strategy item obtained based on the weight corresponding to the target index is a relatively optimal strategy item.

[0015] In a possible implementation, further comprising: obtaining an optimization maximum duration; performing at least one round of iteration based on the information of the optimization region and the weight corresponding to the target index, and ending the iteration when the total duration of performing the at least one round of iteration reaches the optimization maximum duration.

[0016] Optionally, the optimization maximum duration is preset or specified by the management service consumer.

[0017] In the above implementation, by setting the end condition (i.e., the optimization maximum duration), the optimization process can be controlled to improve the optimization efficiency.

[0018] In one possible implementation, obtaining the information of the optimization region includes: receiving a first request message from the management service consumer, the first request message including the information of the optimization region, the first request message being used to request the optimization result corresponding to the optimization region.

[0019] Optionally, the first request message may further include one or more of the following: the weight corresponding to the target indicator, or the indication information of the number of strategy recommendations, or the indication information of the maximum optimization time.

[0020] In one possible implementation, before receiving the first request message from the management service consumer, the method further includes: receiving a second request message from the management service consumer, the second request message being used to request information on the optimization region; and in response to the second request message, selecting an optimization region from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

[0021] In one possible implementation, obtaining the information of the optimization region includes: receiving a third request message from the management service consumer, the third request message being used to request the determination of the optimization region and to obtain the optimization result corresponding to the optimization region; in response to the third request message, selecting the optimization region from the candidate regions according to the index values ​​corresponding to the collected candidate regions.

[0022] Optionally, the third request message may include one or more of the following: the weight corresponding to the target indicator, or the indication information of the number of strategy recommendations, or the indication information of the maximum optimization time.

[0023] In one possible implementation, obtaining the information of the optimization region includes: selecting the optimization region from the candidate regions according to the index values ​​corresponding to the collected candidate regions, based on the optimization cycle.

[0024] In one possible implementation, the optimization area is a portion of the area covered by the operator's network.

[0025] In one possible implementation, the optimization area includes: an area selected from the candidate areas based on the index values ​​corresponding to the collected candidate areas. The candidate areas are areas within the coverage area of ​​the operator's network.

[0026] Optionally, the optimization region may further include: a region adjacent to the region selected from the candidate regions.

[0027] One possible implementation further includes: obtaining the optimization result corresponding to the optimization region based on the network model, wherein the coverage area corresponding to the network model matches the optimization region.

[0028] Optionally, the network model is a digital twin network model.

[0029] In the above implementation, since optimization is performed using a network model (such as a digital twin network model), the impact on the existing network can be reduced compared to optimization within the existing network. Furthermore, using a network model for optimization, especially multi-objective collaborative optimization based on a network model, can improve optimization efficiency.

[0030] Secondly, a communication method is provided, comprising: acquiring information about an optimization region, a target indicator, and indication information of an optimization target, wherein the optimization target indicates the requirements that the optimization result must meet, and the information about the optimization region indicates the optimization region; based on the information about the optimization region and the optimization target, sending the optimization result corresponding to the optimization region to a management service consumer, or configuring the network according to the optimization result; wherein the optimization result includes a first strategy item, the first strategy item including a recommended value of the network parameter corresponding to the target indicator and an indicator value corresponding to the recommended value, and the first strategy item satisfies the optimization target.

[0031] In the above implementation method, on the one hand, since network optimization is based on the optimization area, compared with network optimization across the entire network, the optimization scope can be narrowed, thus improving the efficiency of target optimization. On the other hand, based on the optimization goal, strategy items that meet the requirements of the optimization goal can be recommended to the management service consumer.

[0032] Optionally, the target metric is preset or specified by the management service consumer.

[0033] Optionally, the indication information for the optimization target is preset or specified by the management service consumer.

[0034] In one possible implementation, sending the optimization result corresponding to the optimization region to the management service consumer based on the information of the optimization region and the indication information of the optimization target includes: performing at least one round of iteration based on the information of the optimization region, and when the first strategy item is obtained during the execution of the at least one round of iteration, ending the iteration and sending the optimization result to the management service consumer, wherein the optimization result includes the first strategy item, the first strategy item includes the indicator value of the first indicator, and the indicator value of the first indicator satisfies the requirement.

[0035] In the above implementation, once a strategy item that meets the optimization objective is obtained during the optimization process, the optimization process can be terminated in a timely manner, thus improving optimization efficiency.

[0036] In one possible implementation, the optimization objective is used to indicate the requirements that the optimization result satisfies, including: the optimization objective is used to indicate the requirements that the value of a first indicator satisfies, the first indicator including some or all of the target indicators; the first strategy item satisfies the optimization objective, including: in the first strategy item, the value of the first indicator satisfies the requirements indicated by the optimization objective.

[0037] In one possible implementation, the indication information of the optimization target includes the target value of the first indicator, or the target network performance improvement rate corresponding to the first indicator.

[0038] In one possible implementation, obtaining the information of the optimization region includes: receiving a first request message from the management service consumer, the first request message including the information of the optimization region, the first request message being used to request the optimization result corresponding to the optimization region.

[0039] In one possible implementation, the first request message may also include indication information of the optimization target.

[0040] In one possible implementation, the first request message further includes second indication information, which is used to indicate network configuration based on the optimization result after obtaining the optimization result.

[0041] In one possible implementation, before receiving the first request message from the management service consumer, the method further includes: receiving a second request message from the management service consumer, the second request message being used to request information on the optimization region; and in response to the second request message, selecting an optimization region from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

[0042] In one possible implementation, obtaining the information of the optimization region includes: receiving a third request message from the management service consumer, the third request message being used to request the determination of the optimization region and to obtain the optimization result corresponding to the optimization region; in response to the third request message, selecting the optimization region from the candidate regions according to the index values ​​corresponding to the collected candidate regions.

[0043] In one possible implementation, the third request message includes indication information of the optimization target.

[0044] In one possible implementation, the third request message further includes second indication information, which is used to indicate network configuration based on the optimization result after obtaining the optimization result.

[0045] In one possible implementation, obtaining the information of the optimization region includes: selecting the optimization region from the candidate regions according to the index values ​​corresponding to the collected candidate regions, based on the optimization cycle.

[0046] In one possible implementation, the optimization area is a portion of the area covered by the operator's network.

[0047] In one possible implementation, the optimization region includes: a region selected from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

[0048] Optionally, the candidate area is an area within the coverage area of ​​the operator's network.

[0049] In one possible implementation, the optimization region further includes a region adjacent to the region selected from the candidate regions.

[0050] One possible implementation further includes: obtaining the optimization result corresponding to the optimization region based on the network model, wherein the coverage area corresponding to the network model matches the optimization region.

[0051] Optionally, the network model is a digital twin network model.

[0052] Thirdly, a communication apparatus is provided, comprising a unit or module for performing the method as described in any of the first aspects above, or comprising a unit or module for performing the method as described in any of the second aspects above.

[0053] Fourthly, a communication device is provided, comprising: one or more processors configured to perform the method as described in any one of the first aspects above, or to perform the method as described in any one of the second aspects above.

[0054] Fifthly, a readable storage medium is provided, the readable storage medium storing a program or instructions that, when executed on a communication device, cause the communication device to perform the method as described in any one of the first aspects above, or to perform the method as described in any one of the second aspects above.

[0055] A sixth aspect provides a chip system including a processor for supporting a computer device to implement the method as described in any one of the first aspects above, or to implement the method as described in any one of the second aspects above.

[0056] In a seventh aspect, a program product is provided, the program product comprising a program; when the program is run on a computer, the computer performs the method as described in any one of the first aspects above, or performs the method as described in any one of the second aspects above. Attached Figure Description

[0057] Figure 1 is a schematic diagram of a system architecture provided in an embodiment of this application;

[0058] Figure 2 is a schematic diagram of another system architecture provided in an embodiment of this application;

[0059] Figure 3 is a schematic diagram of another system architecture provided in an embodiment of this application;

[0060] Figure 4 is a flowchart illustrating a communication method provided in an embodiment of this application;

[0061] Figure 5 is a flowchart illustrating another communication method provided in an embodiment of this application;

[0062] Figure 6 is a flowchart illustrating another communication method provided in an embodiment of this application;

[0063] Figure 7 is a flowchart illustrating another communication method provided in an embodiment of this application;

[0064] Figure 8 is a schematic diagram of the structure of a communication device provided in an embodiment of this application;

[0065] Figure 9 is a schematic diagram of another communication device provided in an embodiment of this application;

[0066] Figure 10 is a schematic diagram of another communication device provided in an embodiment of this application. Detailed Implementation

[0067] When planning wireless communication network systems, it is necessary to achieve maximum optimization of target indicators to achieve target optimization. The current target optimization method is to iterate the configuration strategy for target indicators in the existing network.

[0068] Taking the coordinated optimization of terminal experience rate and energy consumption metrics as an example, the traditional method is as follows: First, optimize the network system for the terminal experience rate metric, generate Strategy 1, and distribute it to the live network, waiting for performance feedback from the live network to determine the optimization effect; then, based on the optimization effect of the live network, generate Strategy 2 and distribute it to the live network, iterating in this way until the network system has no room for optimization in the terminal experience rate metric. Next, optimize the network system for the energy consumption metric, generate Strategy 3, and distribute it to the live network, waiting for performance feedback from the live network to determine the optimization effect; then, based on the optimization effect of the live network, generate Strategy 4 and distribute it to the live network, stopping the iteration when the terminal experience rate metric is affected by degradation. This achieves coordinated optimization of terminal experience rate and energy consumption.

[0069] The above process requires iteration across the entire operator's network, resulting in long processing times and low optimization efficiency. When there are multiple optimization targets (such as energy consumption and speed metrics), the time consumption is even longer and the optimization efficiency is even lower due to the network-wide iteration and the sequential iteration of multiple optimization targets.

[0070] Therefore, embodiments of this application provide a communication method and related apparatus for implementing the method, in order to improve the efficiency of target optimization. Embodiments of this application are described below.

[0071] To better understand the embodiments of this application, some terms and technologies involved in the embodiments of this application will be explained below so that those skilled in the art can understand them.

[0072] (I) Performance Indicators of Wireless Communication Network Systems

[0073] Performance metrics (hereinafter referred to as metrics) of wireless communication network systems can be used to evaluate or measure the performance and quality of wireless communication network systems.

[0074] The metrics of a wireless communication network system can be categorized from multiple dimensions of network planning objectives. For example, they can be categorized from multiple dimensions such as energy saving, coverage, capacity, quality, and data service capabilities.

[0075] (1) Indicators related to energy conservation targets

[0076] Indicators related to energy conservation targets can include communication network energy efficiency indicators (also simply called energy efficiency indicators). Energy efficiency indicators are used to evaluate the energy efficiency of wireless communication networks. They can be expressed as the amount of energy consumed per unit of time, such as kilowatt-hours per day. The energy consumption in energy efficiency indicators refers to total energy consumption, which includes the energy consumption of communication equipment and infrastructure. Accordingly, energy efficiency indicators can be broken down into communication equipment energy efficiency indicators and infrastructure energy efficiency indicators. For example, the energy consumption of communication equipment can be quantified as the energy consumed per unit of time, and can be used to assess the energy utilization efficiency and environmental impact of the equipment.

[0077] The method for calculating energy consumption can be adjusted according to the specific communication equipment and application scenario, and typically includes the following aspects:

[0078] a) Energy consumption of communication equipment

[0079] Communication equipment energy consumption refers to the energy consumed by communication equipment during operation, which can be calculated by measuring the equipment's power and operating time. For example, the formula for calculating communication equipment energy consumption can be:

[0080] Energy consumption (kWh) = Power (W) × Operating time (hours) ÷ 1000

[0081] b) System energy consumption

[0082] System energy consumption refers to the energy consumed by the entire communication system during operation. It is related to the interconnection between communication devices and the topology of the communication network. System energy consumption can be calculated by summing the energy consumption of each device in the system.

[0083] c) Communication energy consumption

[0084] Communication energy consumption refers to the energy consumed during communication, which is related to the transmission power, transmission distance, and transmission time of the communication equipment.

[0085] For example, the formula for calculating communication energy consumption can be:

[0086] Energy consumption (kWh) = Transmission power (W) × Transmission time (hours) ÷ 1000

[0087] It should be understood that the above only exemplarily illustrates the indicators related to energy-saving targets and their calculation methods, and this application does not impose any limitations on them.

[0088] (2) Indicators related to data service capability objectives

[0089] The data service capabilities provided by wireless communication networks directly impact user experience. User experience rate is a key metric for measuring data service capabilities and directly influences users' evaluation of network capabilities. The user experience rate metric (hereinafter referred to as rate metric) can be further subdivided into various indicators, such as the cell edge user rate. The cell edge user rate refers to the user experience rate guaranteed within the cell edge area.

[0090] In network planning, different data service capability targets can be defined based on different business scenarios and regional needs. For example, different rate targets can be set for enhanced mobile broadband (eMBB) service scenarios, massive machine-type communication (mMTC) service scenarios, and Internet of Things (IoT) service scenarios.

[0091] (3) Indicators related to capacity targets

[0092] In network planning, the capacity objective is the data throughput capability that the network will achieve after its completion. Network capacity is divided into uplink throughput and downlink throughput. In the capacity calculation of wireless communication networks, uplink throughput and downlink throughput can be combined.

[0093] (4) Indicators related to quality objectives

[0094] From a quality objective perspective, services can be categorized into voice services and data services. For voice services, quality-related metrics may include connection latency and access success rate. For data services, quality-related metrics may include the service channel's frame error rate, bit error rate, throughput, and latency.

[0095] Service connection quality characterizes the speed and ease with which a user can be connected, and can be measured by connection latency and access success rate. Transmission quality reflects the accuracy of the data services received by the user, and can be measured by the frame error rate and bit error rate of the service channel. For data services, throughput and latency can be used to measure service quality.

[0096] (5) Indicators related to coverage targets

[0097] Metrics related to coverage targets can include area coverage, line coverage, and point coverage. Area coverage is the value obtained by dividing the covered area (square kilometers) by the target coverage area (square kilometers). Line coverage is the value obtained by dividing the length of covered roads (kilometers) by the total length of roads (kilometers). Point coverage is the value obtained by dividing the number of covered points by the total number of points. Here, "point" can be understood as a site, such as a base station.

[0098] Based on the above indicators related to the coverage target, the values ​​of the above indicators can be determined by measuring the following parameters: reference signal receiving power (RSRP), reference signal-signal to interference plus noise ratio (RS-SINR), signal to interference ratio (SIR), terminal transmit power, etc.

[0099] RSRP is the received power of the downlink common reference signal, used to reflect the signal strength. RS-SINR represents the ratio of the useful signal to interference and noise floor. RS-SINR can be divided into reference signal RS-SINR and traffic channel SINR. SIR reflects the user channel environment and is correlated with the user experience rate.

[0100] It should be understood that the indicators listed above are merely possible examples, and this application does not limit the types of indicators related to wireless communication network system planning.

[0101] It should also be understood that in the embodiments of this application, the term "indicator" refers to the name of the indicator, and the term "indicator value" refers to the value of the indicator. For example, in "energy efficiency indicator = xx kWh / day", "energy efficiency indicator" is the name of the indicator, and "xx kWh / day" is the value of the indicator. In some embodiments, the indicator and the indicator value have the same meaning and can be used interchangeably.

[0102] (II) Digital Twin Network

[0103] Digital twin networks are used to construct real-time mirrors of physical networks. They are network systems with both physical network entities and virtual twins, allowing for real-time interactive mapping between the two. Within this system, various network management and applications can leverage the virtual twins built using digital twin technology to efficiently analyze, diagnose, simulate, and control the physical network based on data and models. Digital twin networks can enhance the systematic simulation, optimization, verification, and control capabilities lacking in physical networks.

[0104] Network twins can leverage optimization algorithms, management methods, and expert knowledge to analyze, diagnose, simulate, and control physical networks throughout their entire lifecycle. This enables real-time interactive mapping between the physical network and the twin network, helping to deploy various network applications at a lower cost, higher efficiency, and with less impact on the existing network, thus facilitating simplified and intelligent network operation and maintenance.

[0105] In some embodiments of this application, network planning optimization can be performed based on digital twin networks.

[0106] The embodiments of this application will now be described with reference to the accompanying drawings.

[0107] Referring to Figure 1, this is a system architecture provided in an embodiment of this application.

[0108] As shown in Figure 1, the system architecture includes a network management system (NMS) and an element management system (EMS).

[0109] NMS is typically a network management system for mobile operators. NMS is a cross-domain management system, or in other words, NMS can be replaced by a cross-domain management system. NMS can manage multiple EMS. Figure 1 only shows one EMS as an example. This application does not limit the number of EMS managed by NMS.

[0110] EMS is typically a management system for equipment manufacturers. EMS stands for domain management system, or in other words, EMS can be replaced by a domain management system. Generally, one EMS corresponds to one equipment manufacturer, or one equipment manufacturer owns one EMS.

[0111] The NMS and the EMS managed by the NMS can reside in the same operator's operations, administration and maintenance (OAM) system.

[0112] EMS can include performance analysis functional entities and optimization functional entities, or in other words, performance analysis functional entities and optimization functional entities can be deployed in EMS.

[0113] NMS can provide management service interfaces for management service consumers to call. NMS and EMS store communication interfaces. Through these interfaces, management service consumers can interact with the performance analysis and optimization entities within EMS. Optionally, the performance analysis and optimization entities within EMS can communicate with each other through the communication interfaces.

[0114] The aforementioned management service consumers can be located in NMS or vertical industry systems. Management service consumers can be third-party applications or NMS applications; this application does not impose any restrictions in this regard.

[0115] The aforementioned performance analysis function entity can be understood as a service or application. The performance analysis function entity can be implemented in software or a combination of software and hardware; this application does not impose any restrictions on this. The performance analysis function entity can be an independent logical function, implemented through a separate hardware entity (such as a network element), or it can be co-located with other functional entities (such as an optimization function entity) within the same hardware entity.

[0116] The aforementioned optimization function entity can be understood as a service. The optimization function entity can be implemented in software or a combination of software and hardware; this application does not impose any restrictions on this. The optimization function entity can be an independent logical function, which can be implemented through a separate hardware entity (such as a network element) or co-located in the same hardware entity with other functional entities (such as a performance analysis function entity).

[0117] The above division of performance analysis and optimization functions is only one possible example, and this application does not limit it. For example, in another example, the performance analysis and optimization functions in EMS can be implemented through a single entity.

[0118] In the above system architecture, the management service consumer can send a request message to the performance analysis management function entity to request the optimization area. The management service consumer can also send a request message to the optimization function entity to request the optimization results corresponding to the optimization area. The performance analysis function entity can initiate a process to determine the optimization area based on the management consumer's request or independently. In this process, the performance analysis function entity can statistically analyze the network performance indicators of candidate areas based on the requirements of the management service consumer (e.g., indicators specified by the management service consumer), thereby determining the optimization area to be optimized. The optimization function entity can initiate an optimization process based on the request from the management consumer or the performance analysis function entity to optimize the configuration strategy of the wireless communication network system in a simulation environment, obtaining optimization results, which include the network configuration strategy. The optimized configuration strategy can be applied to network elements in the radio access network, thereby optimizing the network. For example, the configuration strategy can be applied to radio access network (RAN) equipment or to network elements in the core network, such as access and mobility management function (AMF) and session management function (SMF).

[0119] Based on the architecture shown in Figure 1, both the performance analysis and optimization functions are deployed in the EMS, meaning that both performance analysis and optimization functions are implemented by the EMS. Since the performance analysis and optimization functions are deployed in an EMS controlled by the equipment manufacturer, the optimization process can be controlled by the equipment manufacturer.

[0120] Referring to Figure 2, another system architecture is provided in an embodiment of this application.

[0121] As shown in Figure 2, this system architecture includes a Network Management System (NMS) and an Element Management System (EMS). For details regarding the NMS, EMS, and service management consumers, please refer to the description of the system architecture shown in Figure 1.

[0122] Unlike the system architecture shown in Figure 1, the system architecture shown in Figure 2 can include performance analysis and optimization functional entities in the NMS, or in other words, performance analysis and optimization functional entities can be deployed in the NMS.

[0123] The above division of performance analysis and optimization functions is only one possible example, and this application does not limit it. For example, in another example, the performance analysis and optimization functions in NMS can be implemented through a single entity.

[0124] Based on the architecture shown in Figure 2, both the performance analysis and optimization functions are deployed in the NMS, meaning that both performance analysis and optimization functions are implemented by the NMS. Since the performance analysis and optimization functions are deployed in an operator-controlled NMS, optimization can be performed under operator control.

[0125] Referring to Figure 3, another system architecture is provided in the embodiments of this application.

[0126] As shown in Figure 3, this system architecture includes a Network Management System (NMS) and a Radio Access Network, or it includes a Network Management System (NMS) and a Core Network, or it includes a Network Management System (NMS), a Radio Access Network, and a Core Network. For details regarding the NMS, EMS, and service management consumers, please refer to the description of the system architecture shown in Figure 1.

[0127] Unlike the system architectures shown in Figures 1 and 2, the system architecture shown in Figure 3 includes a performance analysis function entity within the NMS; in other words, the performance analysis function entity and the optimization function entity can be deployed within the NMS. The NMS can reside within the operator's OAM system.

[0128] The radio access network or core network may include optimization function entities, or optimization function entities may be deployed in network elements in the radio access network, such as base stations, or in network elements in the core network, such as user plane functions (UPFs).

[0129] The NMS can provide a management service interface for management service consumers to call. Through this interface, management service consumers can interact with the performance analysis function entity in the NMS. The optimization function entity in the radio access network (RAN) and the performance analysis function entity in the NMS can communicate via the interface between OAM and RAN network elements (e.g., RAN). The optimization function entity in the core network and the performance analysis function entity in the NMS can communicate via the interface between OAM and core network elements (e.g., UPF). This application does not limit the specific implementation of the above interfaces in its embodiments.

[0130] Based on the architecture shown in Figure 3, the performance analysis function entity is deployed in the NMS, while the optimization function entity is deployed in the radio access network or core network. In other words, both performance metric collection and performance analysis are implemented by the NMS. Since the optimization function entity is deployed in the radio access network or core network, optimization can be controlled by network elements within the radio access network or core network.

[0131] It should be understood that the names of the management service consumer, performance analysis functional entity, and optimization functional entity in the embodiments of this application are only possible examples, and this application does not limit the names of the above functional entities.

[0132] Based on the system architecture shown in Figures 1, 2, or 3 above, Figure 4 shows a flowchart of a communication method provided in an embodiment of this application.

[0133] In the process shown in Figure 4, the management service consumer can first request information such as the optimization region from the performance analysis function entity, and then request the optimization results corresponding to the optimization region from the optimization function entity. Based on the management service consumer's request, the optimization function entity executes the optimization iteration process and returns the statistically analyzed strategy items to the management service consumer.

[0134] Optionally, the number of strategy items returned by the optimization function entity to the management service consumer is the same as the number of strategy recommendations specified. The optimization iteration process and the process of selecting strategy items to be returned to the management service consumer from the obtained strategy items can both be based on the weight of the target indicator.

[0135] In this embodiment, the area within the operator's network coverage can be divided into multiple candidate areas. Candidate areas can be obtained by dividing physical areas; for example, candidate areas may include commercial areas, residential areas, industrial areas, etc. Each area may contain at least one site, which may include network access equipment, such as base stations or remote radio units (RRUs), or other equipment, such as building baseband units (BBUs), etc. This application does not impose any limitations on this. Optionally, the candidate area information can be stored in the OAM (Operating Access Management) database.

[0136] The optimization area can be selected from the candidate areas. The optimization area can be a geographical area, such as a commercial area, residential area, or industrial area. The optimization area can also be a portion of the area covered by the operator's network.

[0137] As shown in Figure 4, the process may include the following steps:

[0138] Step 401: The management service consumer sends a second request message to the performance analysis function entity. The second request message is used to request information about the optimization area.

[0139] Optionally, the second request message may include a target indicator (such as the name of the target indicator). The number of target indicators can be one or more; for example, target indicators may include energy consumption indicators, or a combination of energy consumption indicators and rate indicators, and this application does not impose any limitations on this. The target indicator can be used to statistically analyze candidate regions to determine the optimal region.

[0140] Optionally, the second request message may also include information on constraints, which are used to indicate the conditions that the optimization region must meet.

[0141] In one possible implementation, the constraint information may include the number of regions indication information. Accordingly, the condition that the optimization region should meet is: the K regions with the worst indicators among the candidate regions, where K is the number of regions indicated by the region number indication information.

[0142] In another possible implementation, the constraint information may include tolerance levels. Accordingly, the optimization region should meet the condition that the indicator value in the candidate region meets the tolerance requirement. For example, the tolerance level could be a percentage, such as 10%, and the optimization region should meet the condition that the indicator value in the candidate region is 10% lower than the average indicator value.

[0143] In another possible implementation, the constraint information includes the number of regions and the tolerance. Accordingly, the condition that the optimization region should meet is: among the K candidate regions with the worst index values, the region whose index value meets the tolerance requirement; where K is an integer greater than 1.

[0144] Optionally, the region where the index value meets the tolerance requirement is: the region where the index value is worse than a first value, which is equal to the product of the average of the index values ​​corresponding to the K candidate regions with the worst index values ​​and the first percentage indicated by the tolerance.

[0145] It should be understood that the meaning of "the indicator value is worse than the first value" varies depending on the indicator. For example, if the indicator is rate, then "the indicator value is worse than the first value" means that the rate value is less than the first value; as another example, if the indicator is energy consumption, then "the indicator value is worse than the first value" means that the energy consumption is greater than the first value.

[0146] It should also be understood that the above limitations and information regarding the limitations are merely a few possible examples, and the embodiments of this application do not impose any limitations on them.

[0147] Step 402: After receiving the second request message, the performance analysis function entity selects the optimization region from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

[0148] In this step, the performance analysis function entity can collect metrics from multiple candidate regions, analyze the network performance and quality of these regions based on their corresponding metric values, and select one or more candidate regions for network optimization based on the analysis results. These selected regions are then used as optimization areas. This allows for network optimization targeting areas within the operator's network with currently poor network performance and quality.

[0149] In one possible implementation, the optimization region is the region whose index value meets the constraints selected from the candidate regions. Taking the constraint information including the number of regions and the tolerance as an example, where the number of regions indicates 10 and the tolerance is 10%, the performance analysis function entity can determine the optimization region in the following way: collect the energy consumption of each candidate region, select the 10 candidate regions with the highest energy consumption, calculate the average energy consumption of these 10 candidate regions, and select the regions among these 10 candidate regions whose energy consumption is 10% higher than the average as the optimization region.

[0150] Optionally, after analyzing the network performance and quality of multiple candidate regions based on their corresponding index values, and selecting one or more candidate regions based on the analysis results, the regions adjacent to the selected candidate regions can be determined, and these selected candidate regions and their adjacent regions can be used as optimization regions. For example, in the example above, after selecting regions with energy consumption 10% higher than the average from 10 candidate regions, considering the possibility of neighboring region resource coordination in region optimization, in addition to using these regions with energy consumption 10% higher than the average as optimization regions, their neighboring regions can also be used as optimization regions. This implementation method can appropriately expand the scope of the optimization region, thereby improving the rationality and reliability of the optimization results.

[0151] Optionally, for a candidate region selected from the candidate regions, if there may be related handover operations between the first base station in the candidate region and the second base station in the adjacent region, such as the traffic of the first base station being migrated to the second base station, or the terminal device being switched from the first base station to the second base station, then both the candidate region where the first base station is located and the region where the second base station is located can be used as the optimization region.

[0152] Information regarding the aforementioned constraints (e.g., the number of worst-performing regions and / or tolerance levels) can be obtained from the second request message received by the performance analysis function entity. In other words, the management service consumer specifies the constraints for selecting the optimization region, thus selecting the optimization region that meets the management service consumer's requirements. The aforementioned constraints and their information can also be preset.

[0153] The performance analysis function entity can select an optimization region from the candidate regions based on the collected indicator values ​​corresponding to the candidate regions. Specifically, the performance analysis function entity can collect relevant network parameters of the candidate regions according to pre-set target indicators to determine the corresponding indicator values. Alternatively, the performance analysis function entity can collect relevant network parameters of the candidate regions based on target indicators included in the second request message. For example, if the second request message includes a rate indicator, the performance analysis function entity can collect the rate indicator value of the candidate regions and select the optimization region from the candidate regions based on the rate of the candidate regions.

[0154] It should be understood that when the performance analysis function and the optimization function are combined into one entity, the entity can select the optimization region from multiple candidate regions based on the index values ​​corresponding to multiple candidate regions.

[0155] Step 403: The performance analysis function entity sends a second response message to the management service consumer, which includes information about the optimization area.

[0156] Optionally, the information for the optimization area may include geographical indication information, a list of communities, area identifiers, etc., which can be used to indicate the area.

[0157] Optionally, the second response message may also include optimization instruction information to indicate that optimization needs to be performed based on the optimization area.

[0158] Step 404: The management service consumer sends a first request message to the optimization function entity. The first request message includes information about the optimization area and is used to request the optimization results corresponding to the optimization area.

[0159] In this step, after receiving the second response message, the management service consumer can determine that it needs to initiate an optimization request based on the optimization instruction information carried therein or the optimization area information included in the second response message, and therefore send a first request message to the optimization function entity.

[0160] In one possible implementation, the first request message may also include a target metric (such as the name of the target metric). The target metric can be pre-set or specified by the management service consumer. If there are multiple target metrics, these multiple target metrics form a metric group.

[0161] In one possible implementation, the first request message may further include indication information of network parameters, which is used to indicate the name, type, or threshold of the network parameters.

[0162] For example, the indication information for network parameters may include one or more of the following:

[0163] (1) Thresholds for one or more network parameters. For example, maximum antenna tilt angle, RSRP threshold, maximum transmission power, etc.

[0164] (2) Modeling parameter type, which is associated with one or more network parameters. In other words, network parameters can be indicated by the modeling parameter type. For example, radio frequency modeling parameters, L3 mobility modeling parameters, L2 scheduling modeling parameters, etc.

[0165] (3) Indication information of the optimization algorithm, which is associated with one or more modeling parameter types, and each modeling parameter type is associated with one or more network parameters. In other words, the network parameters can be indicated by the optimization algorithm. The modeling parameters may be preset or determined for different optimization algorithms.

[0166] In one possible implementation, the first request message may further include a strategy recommendation quantity indication information. This information indicates the number of recommended strategy items, and the number of strategy items indicated by the indication information can be one or more, but not exceeding the number of iterations in the optimization process. The optimization function entity can return a corresponding number of strategy items to the management service consumer based on the number of strategy items indicated by the strategy recommendation quantity indication information.

[0167] In one possible implementation, the first request message may also include the weights corresponding to the target metrics. When there are multiple target metrics, each metric may have a corresponding weight among some or all of them; this scenario can be called a multi-objective optimization scenario. For example, target metric A may have a weight of 20%, target metric B a weight of 50%, and target metric C a weight of 30%. In a multi-objective optimization scenario, the weights corresponding to the target metrics can be applied to the optimization process, or they can be applied to selecting the strategy item to be returned to the management service consumer from all iteration rounds obtained from this optimization process. For details, please refer to the following steps.

[0168] One possible special case is when there are multiple target metrics, but one of these metrics has a weight of 100%, while the others have a weight of 0. Another special case is when there is only one target metric. The scenarios corresponding to these two special cases can be called single-objective optimization scenarios. In single-objective optimization scenarios, the network parameter values ​​can be adjusted primarily based on this target metric during the optimization process. When selecting the strategy item to be returned to the management service consumer from all iterations obtained in this optimization process, the target metric can also be the primary selection criterion. For details, please refer to the following steps.

[0169] In one possible implementation, the first request message may further include indication information to indicate either a multi-objective optimization scenario or a single-objective optimization scenario. Optionally, if the indication information indicates a multi-objective optimization scenario, then each of the multiple objective indicators has a corresponding weight; if the indication information indicates a single-objective optimization scenario, then only one of the objective indicators has a weight of 100%, and the weights of the other indicators are 0, or only one of the objective indicators is used as the optimization target for selecting optimization or strategy items.

[0170] In one possible implementation, the first request message may further include an indication of the maximum optimization duration. This indication is used to specify the maximum duration of the optimization process, allowing the optimization function entity to control the optimization process based on this maximum duration, for example, by using it as one of the termination conditions for the optimization process. It should be understood that the termination conditions for the optimization process may also include other conditions, and this application does not limit this.

[0171] Step 405: The optimization function entity determines the optimization result corresponding to the optimization region, which includes strategy items. Each strategy item includes the recommended value of the network parameter and the index value corresponding to the recommended value.

[0172] In some embodiments of this application, to improve optimization efficiency and reduce the impact on the existing network, the optimization function entity can determine a network model based on the optimization area, target indicators, and network parameters that need to be adjusted. An iterative optimization process is then performed based on this network model to obtain the optimization result. The coverage area corresponding to this network model matches the optimization area. For example, this network model can be used to simulate the network environment, network topology, and network element configuration within the optimization area.

[0173] The implementation methods for determining the network model for the optimization function entity may include: selecting a suitable network model from existing network models, such as selecting a network model whose coverage matches the coverage corresponding to the optimization area mentioned above. For example, selecting a network model whose coverage is equal to, slightly smaller than, or close to the optimization area mentioned above; or selecting a network model from existing network models that is closest to the optimization requirements (such as including optimization requirements and target indicators) and modifying the network model to suit the current optimization requirements; or creating a suitable network model based on the optimization area and target indicators.

[0174] Optionally, the network model may be a digital twin network model, a management data analysis service (MDAS) model, a self-organizing network (SON) model, or an artificial intelligence / machine learning model; this application does not impose any limitations on this.

[0175] When optimizing based on a network model, multiple iterations can be performed until the termination condition is met.

[0176] One possible implementation is to use the maximum optimization time as the termination condition. That is, during the optimization process, the iteration ends when the total time of the optimization process reaches the maximum optimization time.

[0177] Optionally, the maximum optimization duration can be preset or specified by the management service consumer. For example, the management service consumer can send the indication information of the maximum optimization duration to the optimization function entity in the first request message.

[0178] In each iteration, the network model can output the optimization result for that iteration, which may include a policy term. Each policy term corresponds to a network configuration policy.

[0179] A strategy item can include recommended values ​​for network parameters corresponding to a target metric, as well as the corresponding metric values. The recommended network parameter values ​​can be understood as the specific content of the network configuration strategy recommended or suggested by the network model, such as configuration parameters for network elements. The metric value indicates the potential performance of the network system if the network is configured according to the recommended values ​​of the network parameters. The metric value can be used to evaluate the network configuration strategy.

[0180] In one possible implementation, information related to the network parameters (e.g., type, name, or threshold) can be pre-set. The optimization function entity can then iterate using the network model based on the pre-set network parameter type, name, or threshold to obtain the recommended value of the network parameter output by the network model. In another possible implementation, the information related to the network parameters (e.g., type, name, or threshold) can also be provided to the optimization function entity by the management service consumer. For example, the first request message sent by the management service consumer to the performance analysis function entity may include indication information about the network parameters, indicating that the network model needs to adjust and output the corresponding network parameters.

[0181] In this embodiment, the strategy item includes an indicator value. This indicator value can be the indicator value corresponding to a target indicator. The target indicator (here referring to the indicator name) can be preset. The optimization function entity can iterate using the network model based on the preset target indicator to obtain the indicator value of the target indicator output by the network model. The target indicator can be provided to the optimization function entity by the management service consumer. For example, the first request message sent by the management service consumer to the optimization function entity may include the target indicator, indicating the target of the network model optimization and the indicator value to be output.

[0182] The number of target indicators can be one or more.

[0183] If there is only one target metric, then one example of a strategy item would be:

[0184] [Index of policy item, target metric and its value, list of network parameters].

[0185] If there are N target metrics (N is an integer greater than 1), then one example of a strategy term would be:

[0186] [Index of strategy item, target metric 1 and its value, target metric 2 and its value, ..., target metric N and its value, network parameter list].

[0187] The index of a policy item is used to uniquely identify a policy item; the network parameter list may include recommended values ​​for one or more network parameters.

[0188] In one possible implementation, during the optimization process in each iteration, the network model uses one of the target metrics as the key metric and the other metrics as co-metrics for optimization, thus obtaining the strategy term corresponding to that iteration. The key metric can be called the primary metric corresponding to the strategy term, and the other metrics can be called co-metrics. For example, when optimizing using energy consumption as the key metric and speed as a co-metric, the network model can set network parameters with meeting energy consumption requirements as the primary objective and meeting speed requirements as the secondary objective. Correspondingly, a strategy term output by the network model includes the values ​​of N target metrics, one of which is the primary metric, and the others are co-metrics. Any one of these N target metrics can be used as the primary metric. If the recommended values ​​of the network parameters included in this strategy term are used for network configuration, the optimization effect of the network system on the primary metric is generally higher than the optimization effect on the co-metrics.

[0189] For example, the optimization result determined by the optimization function entity includes multiple strategy items, which form a strategy item list. The strategy items in this list are obtained by the optimization function entity through statistical analysis of the strategy items obtained in all iteration rounds. The number of strategy items in this list is the same as the number of indicators in the indicator group in the first request message. Each strategy item can be identified as:

[0190] [Primary indicator values, coordinating indicator values, network parameter list].

[0191] The primary and secondary indicators are both from the aforementioned indicator groups. The network parameter list includes recommended values ​​for the network parameters.

[0192] Taking the target indicators, including energy efficiency and rate, as an example, when the network model iterates with energy efficiency as the primary indicator and rate as a secondary indicator, the output strategy term is [Energy Efficiency = x1, Rate = y1, Network Parameter List 1]; when the network model iterates with rate as the primary indicator and energy efficiency as a secondary indicator, the output strategy term is [Rate = y2, Energy Efficiency = x2, Network Parameter List 2]. Here, "x1" and "x2" represent different energy efficiency values, and "y1" and "y2" represent different rate values. The network parameters in Network Parameter List 1 and Network Parameter List 2 have the same names and types, but the recommended value for at least one network parameter in each list may differ.

[0193] In one possible implementation, the optimization entity can perform the optimization process based on the weights of the target indicators. Optionally, when adjusting the values ​​of network parameters, the optimization entity adjusts the network parameters based on the principle that the improvement effect of the target indicator with a higher weight on network performance is greater than that of the target indicator with a lower weight. That is, during the optimization process, when adjusting network parameters, based on the weights corresponding to the target indicators, the optimization entity can ensure as much as possible that the recommended network parameter values ​​have a more significant effect on improving network performance on the target indicator with a higher weight than on the target indicator with a lower weight. For example, if the weight of the energy consumption indicator is higher than the weight of the rate indicator, the recommended value of the network parameter can ensure, as much as possible, that when configuring the network based on the network parameter, the improvement effect of network energy efficiency is higher than, not lower than, or not significantly lower than the improvement effect of rate.

[0194] In one possible implementation, for iterations other than the first iteration, the optimization result (e.g., the strategy term) may also include the rate of change of the indicator. Taking the Mth iteration as an example (M > 1), the rate of change of the indicator in the optimization result of the Mth iteration is the ratio of the first difference to the indicator value in the strategy term obtained in the (M-1)th or Mth iteration, where the first difference is the difference between the indicator value in the strategy term obtained in the Mth iteration and the indicator value in the strategy term obtained in the (M-1)th iteration.

[0195] For example, the strategy item for the (M-1)th iteration is: [Energy efficiency index = x1, energy efficiency index change rate = 2%, rate index = y1, rate index change rate = 3%, network parameter list 1].

[0196] The strategy term for the Mth iteration is: [Energy efficiency index = x2, energy efficiency index change rate = 5%, rate index = y2, rate index change rate = -1%, network parameter list 2].

[0197] The formula for calculating "energy efficiency index change rate = 5%" is (x2-x1) / x1*100%, which means that the energy efficiency index value in the Mth iteration is 5% higher than that in the (M-1)th iteration. The formula for calculating "rate index change rate = -1%" is (y2-y1) / y1*100%, which means that the rate index value in the Mth iteration is 1% lower than that in the (M-1)th iteration.

[0198] Step 406: The performance analysis function entity sends a first response message to the management service consumer entity, which includes the optimization results corresponding to the optimization area.

[0199] In general, multiple iterations are performed in step 405, and each iteration yields an optimization result (which includes a strategy term).

[0200] In one possible implementation, the optimization function entity can send the optimization results obtained in each iteration to the management service consumer. For example, whenever the optimization function entity completes an iteration and obtains the optimization results for that iteration, it can send the optimization results for that iteration to the management service consumer; alternatively, the optimization function entity can wait until all iterations have been completed before sending the optimization results for all iterations to the management service consumer.

[0201] In another possible implementation, the optimization function entity can statistically analyze the optimization results of all iteration rounds and send the statistical results to the management service consumer. After statistically analyzing the optimization results of all rounds, at least two strategy items can be obtained. The number of these at least two strategy items is the same as the number of target indicators. Each strategy item corresponds to a primary indicator, and the primary indicators corresponding to different strategy items are different from each other.

[0202] Taking N target indicators as an example, the optimization result sent by the optimization function entity to the management service consumer includes N strategy items. The first strategy item uses the first indicator among the N target indicators as the primary indicator, the second strategy item uses the second indicator among the N target indicators as the primary indicator, the third strategy item uses the third indicator among the N target indicators as the primary indicator, and so on.

[0203] Optionally, among the strategy items obtained in all iteration rounds, for strategy items that use the same metric as the primary metric, the optimization function entity can select the strategy item with the best metric value for that primary metric. For example, it can select the strategy item with the highest metric value improvement based on the rate of change of the primary metric. In this way, the optimal strategy item can be sent to the management service consumer for each target metric.

[0204] In another possible implementation, the optimization function entity can select the same number of strategy items as the number of strategy recommendations from the strategy items obtained in each iteration round based on the weight of the target indicator, and return the selected strategy items to the management service consumer.

[0205] One implementation of the optimization function entity selecting strategy items based on the weight of the target indicator is as follows: The optimization function entity determines the evaluation value of the strategy items corresponding to each iteration round according to the weight of the target indicator. The evaluation value of the strategy item corresponding to an iteration round is obtained by weighted summation of the indicator values ​​of the target indicator in the strategy items corresponding to that iteration round. Then, the optimization function entity selects the same number of strategy items as the number of strategy recommendations from all strategy items based on the evaluation values ​​of all strategy items.

[0206] For example, among the following six strategy items, the energy-saving improvement rate based on energy consumption indicators and the rate improvement rate based on rate indicators are as follows:

[0207] Strategy 1: Energy saving effect improvement rate of 20% based on energy consumption index, and speed improvement rate of 10% based on speed index;

[0208] Strategy Item 2: Energy saving efficiency improvement rate of 18% based on energy consumption indicators, and speed improvement rate of 11% based on speed indicators;

[0209] Strategy Item 3: Energy saving effect improvement rate of 16% based on energy consumption index, and speed improvement rate of 12% based on speed index;

[0210] Strategy Item 4: Energy saving effect improvement rate of 15% based on energy consumption index, and speed improvement rate of 15% based on speed index;

[0211] Strategy Item 5: Energy saving effect improvement rate of 10% based on energy consumption index, and speed improvement rate of 20% based on speed index;

[0212] Strategy Item 6: Energy saving effect improvement rate of 9% based on energy consumption index, and speed improvement rate of 30% based on speed index.

[0213] Taking the following example where energy consumption indicators have a weight of 80% and rate indicators have a weight of 20%, a weighted sum can be calculated for each strategy item to obtain its evaluation value. For example, the evaluation value for strategy item 1 is calculated as follows:

[0214] (Energy saving efficiency improvement rate * 80% + Speed ​​improvement rate * 20%) * 100 = (20% * 80% + 10% * 20%) * 100 = 18

[0215] Similarly, the evaluation values ​​of other strategy items can also be calculated using the same method.

[0216] The six strategy items are sorted from highest to lowest according to their evaluation scores, resulting in: Strategy Item 1, Strategy Item 2, Strategy Item 3, Strategy Item 4, Strategy Item 5, and Strategy Item 6. Taking a strategy recommendation quantity of 3 as an example, the optimization function entity selects Strategy Item 1, Strategy Item 2, and Strategy Item 3 and returns them to the management service consumer.

[0217] For example, in a single-objective optimization scenario, such as when the energy efficiency indicator has a weight of 100% and other indicators have a weight of 0, the evaluation value of each strategy item can be calculated using the method described above. Based on the evaluation value of each strategy item, the strategy items that need to be returned to the management service function entity are selected. In other words, after sorting the strategy items from largest to smallest according to the network performance improvement rate corresponding to the target indicator with a weight of 100%, the top M strategy items (M being the number of recommended strategies) are selected and returned to the management service consumer.

[0218] In the above implementation, since the number of policy items selected from the policy items obtained in each iteration round is the same as the number of policy recommendations, the network performance improvement effect corresponding to different target indicators can be comprehensively considered based on the weight ratio of each target indicator, and a better policy item can be selected.

[0219] In one possible implementation, the number of strategy recommendations can be preset or specified by the management service consumer. For example, the management service consumer can send the indication information of the number of strategy recommendations to the optimization function entity in the first request message.

[0220] In one possible implementation, the optimization results sent by the optimization function to the management service consumer may also include one or more of the following:

[0221] (1) Number of iterations: The total number of iterations from the start of the optimization iteration to the end of the optimization iteration when the termination condition is met;

[0222] (2) Total iteration duration: The total time from the start of the optimization iteration to the end of the optimization iteration when the termination condition is met;

[0223] (3) Average iteration duration: The total iteration duration divided by the number of iterations.

[0224] By including the above information in the optimization results, the optimization process can be evaluated based on this information.

[0225] Step 407: The management service consumer selects policy items and configures the network according to the selected policy items.

[0226] In one possible implementation, if the policy item in the optimization result received by the management service consumer is unique, the network can be configured according to the recommended value of the network parameter in the policy item, such as configuring the network elements in the optimization area.

[0227] In another possible implementation, if the number of policy items received by the management consumer in the optimization results is multiple, and these multiple policy items are obtained by the optimization function entity based on the policy items of all iteration rounds, then the management service consumer can select the preferred indicator as the primary indicator from the received policy items according to its own preference for the target indicator, and configure the network system according to the recommended values ​​of the network parameters in the policy item. For example, among the multiple policy items sent by the optimization function entity to the management service consumer, there is a policy item with energy consumption as the primary indicator and a policy item with rate as the primary indicator. If the management service consumer prefers the energy consumption indicator, it can select the policy item with energy consumption as the primary indicator and configure the network based on the policy item.

[0228] In another possible implementation, if the optimization results received by the management consumer include policy items for each iteration round, the management service consumer can select the policy item with the highest improvement in that metric from these iteration rounds based on its own preference for the target metric. For example, if the management service consumer prefers energy consumption metrics, it can select the policy item with the highest improvement in energy consumption metrics from all iteration rounds based on the rate of change of the metrics included in the policy items. If the management service consumer's preferred metrics include both energy consumption and speed metrics, and energy consumption metrics have the highest priority, the management service consumer can select the policy item with both a high improvement in energy consumption metrics and a high improvement in speed metrics from all iteration rounds based on the rate of change of the metrics included in the policy items, and configure the network based on that policy item.

[0229] In another possible implementation, if the number of strategy items in the optimization results received by the management consumer is multiple, and these multiple strategy items are selected by the optimization function entity based on the weight of the target indicator, then the management service consumer can choose the strategy item with the highest evaluation value; or it can choose the strategy item with the best network performance improvement effect on the target indicator according to its own preferred target indicator.

[0230] It is understood that the above are merely examples of several implementation methods for managing service consumers to select policy items, and the embodiments of this application do not limit this.

[0231] In the process shown in Figure 4 above, since network optimization is performed based on the optimization area, the optimization range can be narrowed and the efficiency of target optimization can be improved compared to network optimization across the entire network.

[0232] In the process shown in Figure 4 above, steps 401 to 403 are optional. Besides obtaining the optimization region information through steps 401 to 403, in other embodiments, the performance analysis function entity can also select an optimization region from the candidate regions according to a set period and trigger the optimization function entity to determine the optimization result corresponding to the optimization region. In another embodiment, the optimization function entity can optimize a pre-specified region (e.g., a business center, industrial zone, etc.) according to a set period to obtain the optimization result corresponding to that region.

[0233] Based on the system architecture shown in Figures 1, 2, or 3 above, Figure 5 shows a flowchart of another communication method provided in an embodiment of this application.

[0234] In the process shown in Figure 5, the management service consumer can request the performance analysis function entity to determine the optimization area and the performance analysis function entity can trigger the optimization function entity to execute the optimization iteration process.

[0235] Optionally, the number of strategy items returned by the optimization function entity to the management service consumer is the same as the number of strategy recommendations specified. The optimization iteration process and the process of selecting strategy items to be returned to the management service consumer from the obtained strategy items can both be based on the weight of the target indicator.

[0236] In this embodiment, the area within the operator's network coverage can be divided into multiple candidate areas. Candidate areas can be obtained by dividing physical areas; for example, candidate areas may include commercial areas, residential areas, industrial areas, etc. Each area may contain at least one site, which may include network access equipment, such as a base station or RRU, or other equipment, such as a BBU, etc., and this application does not impose any limitations on this. Optionally, the candidate area information can be stored in the OAM (Operational Information Management System).

[0237] The optimization area can be selected from the candidate areas. The optimization area can be a geographical area, such as a commercial area, residential area, or industrial area. The optimization area can also be a portion of the area covered by the operator's network.

[0238] As shown in Figure 5, the process may include the following steps:

[0239] Step 501: The management service consumer sends a third request message to the performance analysis function entity. The third request message is used to request the determination of the optimization area and to obtain the optimization results corresponding to the optimization area.

[0240] Optionally, the third request message may include a target metric (such as the name of the target metric). There may be one or more target metrics. This target metric can be used to statistically analyze candidate regions to determine the optimal region.

[0241] Optionally, the third request message may also include information on constraints, which indicates the conditions that the optimization region must meet. For details regarding the "information on constraints," please refer to step 401 in the flowchart shown in Figure 4.

[0242] Optionally, the third request message may also include indication information for network parameters, which indicates the name, type, or threshold of the network parameters. For details regarding the network parameters, please refer to step 404 in Figure 4.

[0243] Optionally, the third request message may also include first indication information, which is used to instruct the performance analysis function entity to request the optimization result corresponding to the optimization region from the optimization function entity after determining the optimization region.

[0244] In one possible implementation, if the third request message contains first indication information, it indicates that the management service consumer requests the performance analysis function entity to independently request the optimization result corresponding to the optimization region after determining the optimization region. In another possible implementation, the third request message contains first indication information. When the value of the first indication information equals a first value, it indicates that the management service consumer requests the performance analysis function entity to independently request the optimization result corresponding to the optimization region after determining the optimization region; when the value of the first indication information equals a second value, it indicates that the management service consumer instructs the performance analysis function entity to return the optimization region information to the management service consumer after determining the optimization region, and the management service consumer determines whether to request the optimization result corresponding to the optimization region from the optimization function entity. For example, the first value equals 1 and the second value equals 0; or the first value equals 0 and the second value equals 1.

[0245] Since the first instruction information can instruct the performance analysis function entity to autonomously request the optimization result corresponding to the optimization region from the optimization function entity, or in other words, instruct the performance analysis function entity to request the optimization result corresponding to the optimization region from the optimization function entity on behalf of the management service consumer, the first instruction information can also be called autonomous optimization instruction information. This application embodiment does not limit the naming of this instruction information.

[0246] Step 502: After receiving the third request message, the performance analysis function entity selects the optimization region from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

[0247] For details on how this step is implemented, please refer to step 402 in the process shown in Figure 4.

[0248] Step 503: The performance analysis function entity sends a fourth request message to the optimization function entity. The fourth request message includes information about the optimization region and is used to request the optimization results corresponding to the optimization region.

[0249] In this step, after the performance analysis function entity determines the optimization area, it can send a fourth request message to the optimization function entity based on the first instruction information, which includes the information of the optimization area.

[0250] Optionally, the fourth request message may also include a target metric (such as the name of the target metric). The target metric can be pre-set or specified by the management service consumer, such as being obtained from the third request message sent by the management service consumer. If there are multiple target metrics, these multiple target metrics form a metric group.

[0251] Optionally, the fourth request message may also include indication information for network parameters, which indicates the name, type, or threshold of the network parameters. The network parameters may be pre-set or specified by the management service consumer, for example, obtained from a third request message sent by the management service consumer.

[0252] Step 504: The optimization function entity determines the optimization result corresponding to the optimization region, which includes strategy items. Each strategy item includes the recommended value of the network parameter and the index value corresponding to the recommended value.

[0253] For details on how to implement this step, please refer to step 405 in the process shown in Figure 4.

[0254] Step 505: The optimization function entity sends the optimization results corresponding to the optimization area to the performance analysis function entity.

[0255] Optionally, the optimization results may also include information such as the number of iterations, the total duration of iterations, or the average duration of iterations.

[0256] Step 506: The performance analysis function entity sends the optimization results corresponding to the optimization area to the management service consumer.

[0257] Step 507: The service consumer selects a policy item from the policy item list and configures the network according to the selected policy item.

[0258] For details on how to implement this step, please refer to step 407 in the process shown in Figure 4.

[0259] In the process shown in Figure 5 above, since network optimization is performed based on the optimization area, the optimization range can be narrowed and the efficiency of target optimization can be improved compared to network optimization across the entire network.

[0260] Similar to the process shown in Figure 5 above, another possible implementation differs from the process shown in Figure 5 in that: the management service consumer or performance analysis function entity can instruct the optimization function entity to directly send the optimization results corresponding to the optimization region to the management service consumer after obtaining them. Accordingly, the optimization function entity can send the optimization results corresponding to the optimization region to the management service consumer without needing to forward them through the performance analysis function entity.

[0261] Based on the system architecture shown in Figures 1, 2 or 3 above, Figure 6 shows a flowchart of a communication method provided in an embodiment of this application.

[0262] In the process shown in Figure 6, the management service consumer can first request information such as the optimization region from the performance analysis function entity, and then request the optimization results corresponding to the optimization region from the optimization function entity. Based on the management service consumer's request, the optimization function entity executes the optimization iteration process and returns the statistically analyzed strategy items to the management service consumer.

[0263] Optionally, the number of strategy items returned by the optimization function entity to the management service consumer is the same as the number of strategy recommendations specified. The optimization iteration process and the process of selecting strategy items to be returned to the management service consumer from the obtained strategy items can both be based on the weight of the target indicator.

[0264] In this embodiment, the area within the operator's network coverage can be divided into multiple candidate areas. Candidate areas can be obtained by dividing physical areas; for example, candidate areas may include commercial areas, residential areas, industrial areas, etc. Each area may contain at least one site, which may include network access equipment, such as a base station or RRU, or other equipment, such as an indoor BBU, etc. This application does not impose any limitations on this. Optionally, the candidate area information can be stored in the OAM (Operational Information Management System).

[0265] The optimization area can be selected from the candidate areas. The optimization area can be a geographical area, such as a commercial area, residential area, or industrial area. The optimization area can also be a portion of the area covered by the operator's network.

[0266] As shown in Figure 6, the process may include the following steps:

[0267] Step 601: The management service consumer sends a second request message to the performance analysis function entity. The second request message is used to request information about the optimization area.

[0268] Step 602: After receiving the second request message, the performance analysis function entity selects the optimization region from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

[0269] Step 603: The performance analysis function entity sends a second response message to the management service consumer, which includes information about the optimization area.

[0270] The specific implementation of steps 601 to 603 above can be referred to steps 401 to 403 in the process shown in Figure 4.

[0271] Step 604: The management service consumer sends a first request message to the optimization function entity. The first request message includes information about the optimization area and is used to request the optimization results corresponding to the optimization area.

[0272] Optionally, the first request message includes indication information of the optimization objective, which is used to indicate the optimization objective. The optimization objective is used to indicate the requirements that the optimization result must meet. For example, the optimization objective is used to indicate the requirements that the value of a first indicator must meet, where the first indicator includes some or all of at least two target indicators.

[0273] Optionally, the indication information for the optimization objective may include the target value of the first indicator. For example, if the indication information for the optimization objective is the target value of the energy consumption indicator, it means that the energy consumption indicator value in the optimized strategy item needs to reach this target value, or that the optimized strategy item (e.g., the recommended value of network parameters) needs to ensure that its energy consumption indicator reaches this target value. As another example, the indication information for the optimization objective may include the target values ​​of both the energy consumption indicator and the rate indicator, meaning that the energy consumption indicator and the rate indicator values ​​in the optimized strategy item need to reach their respective target values, or that the optimized strategy item (e.g., the recommended value of network parameters) needs to ensure that both its energy consumption indicator and rate indicator reach their respective target values.

[0274] For example, if the target value of the energy consumption indicator is x kWh / day, then the value of the energy consumption indicator in the optimized strategy item should be greater than or equal to x kWh / day.

[0275] Optionally, the indication information for the optimization objective includes the target network performance improvement rate corresponding to the first indicator. For example, the indication information for the optimization objective is the target network performance improvement rate based on the energy consumption indicator, indicating that the network performance improvement rate (e.g., energy saving improvement rate) corresponding to the energy consumption indicator in the optimized strategy items needs to reach the target network performance improvement rate, or in other words, the optimized strategy items (e.g., recommended values ​​of network parameters) need to ensure that the network performance improvement rate in terms of energy consumption is achieved. As another example, the indication information for the optimization objective includes the network performance improvement rate corresponding to the energy consumption indicator and the network performance improvement rate corresponding to the speed indicator, indicating that the network performance improvement rates corresponding to the energy consumption indicator and the speed indicator in the optimized strategy items need to reach their respective target network performance improvement rates, or in other words, the optimized strategy items (e.g., recommended values ​​of network parameters) need to ensure that the network performance improvement rates corresponding to both the energy consumption indicator and the speed indicator reach their respective target network performance improvement rates.

[0276] For example, if the energy saving improvement rate corresponding to the energy consumption index is 10%, then the improvement rate corresponding to the energy consumption index in the optimized strategy item should be greater than or equal to 10%.

[0277] In one possible implementation, the first request message may also include a target metric (such as the name of the target metric). The target metric can be pre-set or specified by the management service consumer. If there are multiple target metrics, these multiple target metrics form a metric group.

[0278] In one possible implementation, the first request message may further include indication information for network parameters, which indicates the name, type, or threshold of the network parameters. For details regarding the network parameters, please refer to the relevant content in the flowchart shown in Figure 4.

[0279] Step 605: The optimization function entity performs the optimization process based on the information of the optimization region to obtain the first strategy term that satisfies the optimization objective.

[0280] In this step, the optimization entity performs at least one round of iterations based on the information of the optimization region, and ends the iteration when a first strategy term is obtained during the iteration process. The first strategy term includes the index value of a first indicator, and the index value of the first indicator satisfies the requirements of the optimization objective. That is, during the iteration process, once the optimization entity obtains a strategy term that satisfies the optimization objective, it can stop the iteration and take the strategy term that satisfies the optimization objective as the optimization result.

[0281] Taking the target value of the energy consumption index as an example, when the optimization function entity obtains the first strategy item during the optimization process, and the value of the energy consumption index in the first strategy item is greater than or equal to the target index value, the first strategy item is taken as the optimization result and the optimization process ends.

[0282] For details on how the optimization function entity performs the optimization process, please refer to step 405 in the process shown in Figure 4.

[0283] The following process can include two options: Option 1 and Option 2. Using Option 1, the optimization entity can send the optimized policy item to the management service consumer, which then configures the network based on that policy item. Using Option 2, the optimization entity can configure the network based on the optimized policy item.

[0284] Optionally, the first request message sent by the management service consumer to the optimization function entity may include second instruction information. This second instruction information instructs the optimization function entity to execute the process corresponding to the second option after obtaining a policy item that satisfies the optimization objective, i.e., to perform network configuration based on that policy item. If the first request message does not contain the second instruction information, the optimization function entity executes the process corresponding to the first option after obtaining a policy item that satisfies the optimization objective.

[0285] Optionally, the first request message sent by the management service consumer to the optimization function entity may include third indication information. If the value of the third indication information is the first value, the optimization function entity executes the process corresponding to the second option after obtaining the strategy item that satisfies the optimization objective. If the value of the third indication information is the second value, the optimization function entity executes the process corresponding to the first option after obtaining the strategy item that satisfies the optimization objective.

[0286] The procedures for Option 1 and Option 2 are explained below.

[0287] Referring to Figure 6, the process corresponding to option one may include the following steps:

[0288] Step 606a: The optimization function entity sends the optimization results corresponding to the optimization region to the management service consumer. The optimization results include the first strategy item.

[0289] Optionally, the optimization function entity can also send one or more of the following to the management service consumer: the number of iteration rounds, the total duration of iterations, and the average duration of iterations.

[0290] Step 607a: The management service consumer configures the network according to the first policy item.

[0291] Referring to Figure 6, the process corresponding to Option 2 may include the following steps:

[0292] Step 606b: The optimization function entity performs network configuration according to the first strategy item.

[0293] Step 607b: The optimization function entity sends the optimization result corresponding to the optimization region to the management service consumer. The optimization result includes a first policy item to notify the management service consumer that the network configuration has been performed according to the first policy item. Optionally, the optimization result may also include one or more of the following: the number of iteration rounds, the total duration of iterations, and the average duration of iterations.

[0294] Step 607b is an optional step.

[0295] In the process shown in Figure 6 above, since network optimization is performed based on the optimization region, the optimization range can be narrowed and the efficiency of target optimization can be improved compared to network optimization across the entire network.

[0296] In the process shown in Figure 6 above, steps 601 to 603 are optional. Besides obtaining the optimization region information through steps 601 to 603, in other embodiments, the performance analysis function entity can also select an optimization region from the candidate regions according to a set period and trigger the optimization function entity to determine the optimization result corresponding to the optimization region. In another embodiment, the optimization function entity can optimize a pre-specified region (e.g., a business center, industrial zone, etc.) according to a set period to obtain the optimization result corresponding to that region.

[0297] Figure 7 is a flowchart illustrating another communication method provided in an embodiment of this application. In the flowchart shown in Figure 7, the management service consumer can request the performance analysis function entity to determine the optimization region and obtain the optimization result corresponding to that region. After the performance analysis function entity determines the optimization region, it can independently request the optimization function entity to obtain the optimization result based on the aforementioned request from the management service consumer function entity. Based on the request from the performance analysis function entity, the optimization function entity executes an iterative optimization process. After obtaining a strategy item that meets the optimization objective requirements, it can configure the network according to the strategy item, or send the strategy item to the management service consumer for network configuration.

[0298] The specific implementation methods of steps 704, 705a, and 706a, as well as steps 705b and 706b in the process shown in Figure 7 can be found in the relevant steps in Figure 6.

[0299] The implementation of steps 701 to 703 in the process shown in Figure 7 can be referenced to steps 501 to 503 in the process shown in Figure 5. Specifically, the fourth request message sent by the performance analysis function entity to the optimization function entity may include indication information of the optimization target.

[0300] In the process shown in Figure 7 above, since network optimization is performed based on the optimization region, the optimization range can be narrowed and the efficiency of target optimization can be improved compared to network optimization across the entire network.

[0301] It is understood that, in order to achieve the functions in the above embodiments, the network device and terminal device include hardware structures and / or software modules corresponding to perform each function. Those skilled in the art should readily recognize that, based on the units and method steps of the various examples described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0302] Figures 8 and 9 are schematic diagrams illustrating possible communication devices provided in embodiments of this application. These communication devices can be used to implement the functions of related devices (e.g., performance analysis functional entities, optimization functional entities, or service management consumers) in the above method embodiments, and thus can also achieve the beneficial effects of the above method embodiments. In the embodiments of this application, the communication device can be the above-mentioned device or a module (such as a chip) within the above-mentioned device.

[0303] As shown in Figure 8, the communication device 800 includes a processing unit 810 and a transceiver unit 820. The communication device 800 is used to implement the functions of the related devices in the method embodiments shown in any of the figures 4, 5, 6 or 7 above.

[0304] When the communication device 800 is used to implement the function of the optimization function entity in the method embodiment shown in Figure 4 or Figure 5: the processing unit 810 is used to obtain information about the optimization region, the target indicator, the weight corresponding to the target indicator, and the number of recommended strategies, wherein the information about the optimization region indicates the optimization region; and, based on the information about the optimization region, the weight corresponding to the target indicator, and the number of recommended strategies, the processing unit 820 sends the optimization result corresponding to the optimization region to the management service consumer, wherein the optimization result includes at least one strategy item, the number of the at least one strategy item is the same as the number of recommended strategies, and each strategy item in the at least one strategy item includes a recommended value of the network parameter corresponding to the target indicator and an indicator value corresponding to the recommended value.

[0305] When the communication device 800 is used to implement the function of the optimization function entity in the method embodiment shown in FIG6 or FIG7: the processing unit 810 is used to obtain information of the optimization area, target indicators, and indication information of the optimization target, wherein the optimization target is used to indicate the requirements that the optimization result meets, and the information of the optimization area indicates the optimization area; and, based on the information of the optimization area and the optimization target, the processing unit 820 sends the optimization result corresponding to the optimization area to the management service consumer, or performs network configuration according to the optimization result; wherein the optimization result includes a first strategy item, the first strategy item includes a recommended value of the network parameter corresponding to the target indicator and an indicator value corresponding to the recommended value, and the first strategy item satisfies the optimization target.

[0306] A more detailed description of the processing unit 810 and the transceiver unit 820 can be obtained directly from the relevant descriptions in the method embodiments shown in the above figures, and will not be repeated here.

[0307] Some embodiments of this application provide a communication device 900, which includes a processing circuit 910. The processing circuit 910 may include one or more processors, or all or part of the circuitry in one or more processors for control or processing functions.

[0308] The communication device 900 may also include a communication circuit 920.

[0309] The communication circuit 920 can be a transceiver, a transceiver circuit, or an interface circuit. When the communication device 900 is a chip used in the device, the communication circuit 920 can be a transceiver circuit or an interface circuit. Alternatively, the communication circuit can be a transceiver circuit or an interface circuit.

[0310] Optionally, the communication device 900 may also include a memory 930. The memory 930 is used to store instructions executed by the processor, or to store input data required by the processor to run the instructions, or to store data generated after the processor runs the instructions.

[0311] When the communication device 900 is used to implement the method shown in the above figures, the processor is used to implement the functions of the processing unit and the communication circuit is used to implement the functions of the transceiver unit.

[0312] When the communication device 900 is a chip applied to the aforementioned device, the chip implements the functions of the corresponding device in the above method embodiments. The chip receives information from other modules (such as radio frequency modules or antennas) in the device, which is sent to the device by other devices; or, the chip sends information to other modules (such as radio frequency modules or antennas) in the device.

[0313] It is understood that the processor in the embodiments of this application may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor may be a microprocessor or any conventional processor.

[0314] This application provides another example of a communication device, which includes at least one processor and at least one memory coupled together. The at least one processor is used to store instructions, which, when executed by the at least one processor, cause the communication device to perform the methods described in the above embodiments. Taking a communication device including a processor and a memory as an example, as shown in FIG10, the communication device 1000 includes a processor 1010 and a memory 1030. The processor 1010 and the memory 1030 are coupled together. The memory 1030 stores instructions, and when the instructions stored in the memory 1030 are executed by the processor 1010, the communication device 1000 performs the methods performed by the related devices in the above embodiments.

[0315] It should be understood that the processor 1010 and the memory 1030 can also be integrated together, for example, integrated into a single chip.

[0316] The method steps in the embodiments of this application can be implemented in hardware or in software instructions executable by a processor. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. The storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Alternatively, the ASIC can reside in a network-side device or a terminal-side device. The processor and storage medium can also exist as discrete components in a network-side device or a terminal-side device.

[0317] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a server, a network device, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video optical disc; or it can be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both types of storage media.

[0318] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0319] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. In the textual description of this application, the character " / " generally indicates an "or" relationship between the preceding and following related objects; in the formulas of this application, the character " / " indicates a "division" relationship between the preceding and following related objects. "Including at least one of A, B, and C" can mean: including A; including B; including C; including A and B; including A and C; including B and C; including A, B, and C.

[0320] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The order of the process numbers described above does not imply the order of execution; the execution order of each process should be determined by its function and internal logic.

Claims

1. A communication method, characterized in that, include: Obtain information about the optimization region, target indicators, weights corresponding to the target indicators, and the number of strategy recommendations; the information about the optimization region indicates the optimization region. Based on the information of the optimization region, the weight corresponding to the target indicator, and the number of strategy recommendations, the optimization results corresponding to the optimization region are sent to the management service consumer. The optimization results include at least one strategy item, the number of the at least one strategy item is the same as the number of strategy recommendations, and each strategy item includes a recommended value of the network parameter corresponding to the target indicator and an indicator value corresponding to the recommended value.

2. The method as described in claim 1, characterized in that, The step of sending the optimization results corresponding to the optimization region to the management service consumer based on the information of the optimization region, the weight corresponding to the target indicator, and the number of strategy recommendations includes: Based on the weights corresponding to the target indicators, the evaluation values ​​of the strategy items corresponding to all iteration rounds are determined respectively. The evaluation value of the strategy item corresponding to any iteration round is obtained by weighted summation of the indicator values ​​of the target indicators in the strategy item corresponding to any iteration round. Based on the evaluation values ​​of the strategy items corresponding to all iteration rounds, select the same number of strategy items as the recommended number from the strategy items corresponding to all iteration rounds; The optimization results corresponding to the optimization region are sent to the management service consumer. The optimization results include a number of strategy items selected from the strategy items corresponding to all iteration rounds, which are the same as the number of strategy recommendations.

3. The method according to any one of claims 1-2, characterized in that, Also includes: Get the maximum optimization time; Based on the information of the optimization region and the weights corresponding to the target index, at least one round of iteration is performed, and the iteration ends when the total duration of the at least one round of iteration reaches the maximum optimization duration.

4. The method according to any one of claims 1-3, characterized in that, The process of obtaining information about the optimization region includes: A first request message is received from the management service consumer. The first request message includes information about the optimization region and is used to request the optimization result corresponding to the optimization region.

5. The method as described in claim 4, characterized in that, The first request message may also include one or more of the following: the weight corresponding to the target indicator, or the indication information of the number of strategy recommendations, or the indication information of the maximum optimization time.

6. The method according to any one of claims 4-5, characterized in that, Before receiving the first request message from the management service consumer, the method further includes: Receive a second request message from the management service consumer, the second request message being used to request information about the optimization area; In response to the second request message, an optimal region is selected from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

7. The method according to any one of claims 1-3, characterized in that, The process of obtaining information about the optimization region includes: Receive a third request message from the management service consumer, the third request message being used to request the determination of the optimization region and to obtain the optimization result corresponding to the optimization region; In response to the third request message, an optimal region is selected from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

8. The method as described in claim 7, characterized in that, The third request message includes one or more of the following: the weight corresponding to the target indicator, or the indication information of the number of strategy recommendations, or the indication information of the maximum optimization time.

9. The method according to any one of claims 1-3, characterized in that, The process of obtaining information about the optimization region includes: According to the optimization cycle, the optimization region is selected from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

10. The method according to any one of claims 1-9, characterized in that, The optimization area refers to a portion of the area covered by the operator's network.

11. The method according to any one of claims 1-10, characterized in that, The optimization region includes: the region selected from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

12. The method as described in claim 11, characterized in that, The optimization region also includes regions adjacent to the regions selected from the candidate regions.

13. The method according to any one of claims 1-12, characterized in that, Also includes: The optimization result corresponding to the optimization region is obtained based on the network model, wherein the coverage area corresponding to the network model matches the optimization region.

14. The method as described in claim 13, characterized in that, The network model is a digital twin network model.

15. A communication method, characterized in that, include: The information of the optimization region, target indicators, and indication information of the optimization target are obtained. The optimization target is used to indicate the requirements that the optimization result must meet, and the information of the optimization region indicates the optimization region. Based on the information of the optimization region and the optimization objective, the optimization result corresponding to the optimization region is sent to the management service consumer, or the network is configured according to the optimization result; wherein, the optimization result includes a first strategy item, the first strategy item includes a recommended value of the network parameter corresponding to the target indicator and an indicator value corresponding to the recommended value, and the first strategy item satisfies the optimization objective.

16. The method as described in claim 15, characterized in that, The step of sending the optimization results corresponding to the optimization region to the management service consumer based on the information of the optimization region and the indication information of the optimization target includes: Based on the information of the optimization region, at least one round of iteration is performed, and when the first strategy item is obtained during the execution of the at least one round of iteration, the iteration ends and the optimization result is sent to the management service consumer. The optimization result includes the first strategy item, the first strategy item includes the indicator value of the first indicator, and the indicator value of the first indicator meets the requirements.

17. The method according to any one of claims 15-16, characterized in that, The optimization objective is used to indicate the requirements that the optimization result meets, including: the optimization objective is used to indicate the requirements that the indicator value of the first indicator meets, wherein the first indicator includes some or all of the target indicators; The first strategy item satisfies the optimization objective, including: in the first strategy item, the index value of the first indicator satisfies the requirements indicated by the optimization objective.

18. The method according to any one of claims 15-17, characterized in that, The indication information of the optimization target includes the target value of the first indicator, or the target network performance improvement rate corresponding to the first indicator.

19. The method according to any one of claims 15-18, characterized in that, The process of obtaining information about the optimization region includes: A first request message is received from the management service consumer. The first request message includes information about the optimization region and is used to request the optimization result corresponding to the optimization region.

20. The method as described in claim 19, characterized in that, The first request message also includes indication information of the optimization target.

21. The method according to any one of claims 19-20, characterized in that, The first request message also includes second indication information, which is used to indicate that network configuration should be performed based on the optimization result after the optimization result is obtained.

22. The method according to any one of claims 19-21, characterized in that, Before receiving the first request message from the management service consumer, the method further includes: Receive a second request message from the management service consumer, the second request message being used to request information about the optimization area; In response to the second request message, an optimal region is selected from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

23. The method according to any one of claims 15-18, characterized in that, The process of obtaining information about the optimization region includes: Receive a third request message from the management service consumer, the third request message being used to request the determination of the optimization region and to obtain the optimization result corresponding to the optimization region; In response to the third request message, an optimal region is selected from the candidate regions based on the index values ​​corresponding to the collected candidate regions.

24. The method as described in claim 23, characterized in that, The third request message includes indication information of the optimization target.

25. The method according to any one of claims 23-24, characterized in that, The third request message also includes second indication information, which is used to indicate that network configuration should be performed based on the optimization result after the optimization result is obtained.

26. A communication device, characterized in that, It includes units or modules for performing the method as described in any one of claims 1-14, or includes units or modules for performing the method as described in any one of claims 15-25.

27. A communication device, characterized in that, include: One or more processors are configured to perform the method as described in any one of claims 1-14, or to perform the method as described in any one of claims 15-25.

28. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed on the communication device, cause the communication device to perform the method as described in any one of claims 1-14, or the method as described in any one of claims 15-25.

29. A chip system, characterized in that, Includes a processor for supporting a computer device in implementing the method as claimed in any one of claims 1-14, or in implementing the method as claimed in any one of claims 15-25.

30. A program product, characterized in that, The program product includes a program; when the program is run on a computer, it causes the computer to perform the method as described in any one of claims 1-14, or to perform the method as described in any one of claims 15-25.

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