Centralized wireless access network planning method and device
By introducing weighted undirected graphs and the Louvain algorithm into C-RAN networking, the inefficiency caused by relying on engineering experience in existing technologies is solved, and a highly cohesive and loosely coupled wireless access network planning is achieved, improving the accuracy and efficiency of planning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- XINYANG BRANCH HENAN CO LTD OF CHINA MOBILE COMM CORP
- Filing Date
- 2026-01-29
- Publication Date
- 2026-05-12
AI Technical Summary
Existing C-RAN network planning lacks quantitative models and relies on engineering experience, resulting in low planning efficiency and high consumption of human and material resources, and it cannot achieve high cohesion and low coupling in radio access network planning.
A weighted undirected graph based on base station network element traffic and handover request count is adopted, and the Louvain algorithm is used for partitioning to generate a C-RAN networking scheme with high cohesion and low coupling. The scheme is optimized by maximizing modularity and minimizing vertex weight variance.
It improves the accuracy and efficiency of wireless access network planning, realizes C-RAN networking with high service cohesion and low coupling, and enhances the digital accuracy and efficiency of planning.
Smart Images
Figure CN122028058A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of wireless communication technology, and in particular to a centralized wireless access network planning method and apparatus. Background Technology
[0002] Existing C-RAN networking planning schemes primarily rely on non-quantitative empirical judgments based on factors such as the physical distance between base stations, transmission routing structure, and the actual on-site road network environment. This mainly involves non-quantitative empirical C-RAN networking planning where services conform to engineering requirements: through site surveys of existing network equipment rooms, sites with good equipment room conditions, convenient power supply, and fiber optic deployment are selected as target equipment rooms, and approximately 5-10 surrounding sites are integrated into the target equipment room to form a unified C-RAN network.
[0003] The existing technology has the following main drawbacks: Service follows engineering: The current C-RAN networking is mainly based on engineering implementation, while taking into account service performance. Through surveying existing network equipment rooms, sites with better equipment room conditions, convenient power supply and fiber optic deployment are selected as target equipment rooms. 5-10 surrounding sites are then integrated into the target equipment room to form a C-RAN network cluster. Non-quantitative planning: C-RAN networking does not have a standard quantitative model. It is only constrained by engineering implementation, such as the capacity of C-RAN equipment room racks, fiber optic capacity, and battery capacity. Based on the principle of convenient transmission routing, the surrounding sites that can be accommodated are subjectively qualitatively combined into C-RAN network clusters. Traditional methods are inefficient: Traditional C-RAN planning methods do not have a unified model, so they require site-by-site surveys, which rely on the experience of staff and consume a lot of manpower and resources. Summary of the Invention
[0004] In view of this, this application provides a centralized wireless access network planning method and apparatus to solve the above-mentioned technical problems.
[0005] In a first aspect, embodiments of this application provide a centralized wireless access network planning method, including: A weighted undirected graph is constructed with base station network elements as vertices and user handover between base station network elements as edges; where the vertex weight is the traffic volume of the base station network element and the edge weight is the number of handover requests by the user between base station network elements. The vertices of the weighted undirected graph are partitioned based on edge weights, resulting in multiple candidate partitioning schemes; The vertices of the weighted undirected graph are divided into multiple groups based on the candidate partitioning scheme, and the variance of the vertex weights of all groups is calculated. The candidate partitioning scheme corresponding to the minimum value among the multiple vertex weight variances is determined as the planning scheme for the centralized wireless access network.
[0006] In one possible implementation, the vertices of the weighted undirected graph are partitioned based on edge weights, resulting in multiple candidate partitioning schemes; including: Step S1: Determine a vertex as a group; Step S2: Select a target vertex from any group, and merge the group containing the target vertex with the group containing the adjacent vertices of the target vertex to obtain multiple merged groups; Step S3: The optimal merged group is determined by ensuring that the total business volume of the merged group does not exceed a preset threshold and that the module degree increment of the merged group is the largest. Step S4: Based on the optimal merged grouping, determine the current multiple groups of the weighted undirected graph; Step S5: Determine the sum of the modularity of all current groups as the current Q value; Step S6: Determine whether the current Q value is greater than the previous Q value. If not, proceed to step S2; otherwise, proceed to step S7. Step S7: Determine the current partitioning methods of multiple groups as candidate partitioning schemes.
[0007] In one possible implementation, the steps for calculating the modularity increment of the merged group include: The module degree increment of the merged group is calculated using the following formula. :
[0008] in, It is the sum of the edge weights within the merged group; It is the sum of the weights of the edges associated with the merged group; It is the sum of the weights of the edges connected to the target vertex i within the merged group; It is the sum of the weights of the edges connecting to the target vertex i; It is the sum of the weights of the edges in a weighted undirected graph.
[0009] In one possible implementation, the sum of the modularity of all current groups is calculated, including: The total modularity of all current groups is calculated using the following formula. ;
[0010] in, The number of groups, It is the sum of the edge weights within the group. It is the sum of the weights of the edges in the group association. It is the sum of the weights of the edges in a weighted undirected graph.
[0011] In one possible implementation, the variance of vertex weights for all groups is calculated, including: Calculate grouping The sum of the weights of the vertices ; The number of groups; Calculate the vertex weight variance for all groups. : .
[0012] Secondly, this application provides a centralized wireless access network planning device, comprising: A unit is established to construct a weighted undirected graph with base station network elements as vertices and user handover between base station network elements as edges; wherein, the vertex weight is the traffic volume of the base station network element, and the edge weight is the number of handover requests by the user between base station network elements. The optimization unit is used to partition the vertices of a weighted undirected graph based on edge weights, and obtain multiple candidate partitioning schemes. The computational unit is used to partition the vertices of the weighted undirected graph based on the candidate partitioning scheme, obtain multiple groups, and calculate the variance of the vertex weights of all groups. The determination unit is used to determine the candidate partitioning scheme corresponding to the minimum value among multiple vertex weight variances as the planning scheme for the centralized wireless access network.
[0013] Thirdly, embodiments of this application provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method of embodiments of this application.
[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the methods of embodiments of this application.
[0015] Fifthly, embodiments of this application provide a computer program product, including a computer program / instructions, which, when executed by a processor, implement the method of embodiments of this application.
[0016] This application improves the accuracy and efficiency of centralized wireless access network planning. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0018] Figure 1 This is a schematic diagram of a C-RAN wireless cellular network provided in an embodiment of this application; Figure 2 A flowchart of a centralized wireless access network planning method provided in an embodiment of this application; Figure 3 A schematic diagram of a weighted undirected graph of a wireless network provided in an embodiment of this application; Figure 4 This is a schematic diagram of the local optimization results of Louvain provided in the embodiments of this application; Figure 5 Functional structure diagram of the centralized wireless access network planning device provided in the embodiments of this application; Figure 6 This is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.
[0020] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.
[0021] First, a brief introduction to the design concept of the embodiments of this application will be given.
[0022] Centralized Radio Access Network (C-RAN) networking technology can improve data center security, simplify data center networking structure, and reduce operation and maintenance costs. On the other hand, it is more conducive to the deployment of new technologies such as edge computing. like Figure 1As shown, a key step in C-RAN networking is to unify and merge multiple adjacent base station site equipment rooms in the existing network using fiber optic telemetry. This improves the performance of the merged equipment room by enhancing its power supply, security, computing, and heat dissipation capabilities, while simultaneously reducing the number of forwarding nodes. However, the merging of adjacent sites must take into account the coupling between them. For example, sites with a high frequency of handover between two adjacent sites are considered to have a high coupling relationship, while sites with a low frequency of handover between two adjacent sites are considered to have a low coupling relationship. A reasonable C-RAN network can maximize the merging of adjacent sites with a high coupling relationship and minimize the frequent handover of services between C-RAN nodes.
[0023] To address the technical issues of existing C-RAN networking methods, this application introduces an improved Louvain algorithm based on the capacity limitations of wireless network equipment rooms. It utilizes modularity for network-wide convergence calculations and outputs the optimal C-RAN networking solution through balanced variance decision-making. This method promotes the transformation of C-RAN networking planning from an engineering implementation-centric approach to a service performance-centric approach. Through a quantitative planning model, it achieves the goals of high cohesion and low coupling in C-RAN networking, significantly improving planning accuracy and efficiency.
[0024] This application makes non-quantitative empirical judgments based on factors such as the physical distance between base stations, transmission routing structure, and the actual road network environment on site. The main focus is on the non-quantitative C-RAN network planning that ensures service compliance with engineering requirements. Through site surveys of existing network equipment rooms, sites with good equipment room conditions, convenient power supply, and easy fiber optic deployment are selected as target equipment rooms. Five to ten surrounding sites are then integrated into the target equipment room to form a unified C-RAN network.
[0025] After introducing the application scenarios and design concepts of the embodiments of this application, the technical solutions provided by the embodiments of this application will be described below.
[0026] like Figure 2 As shown, this application embodiment provides a centralized wireless access network planning method, including: Step 101: Establish a weighted undirected graph with base station network elements as vertices and user handover between base station network elements as edges; where the vertex weight is the traffic volume of the base station network element and the edge weight is the number of handover requests by the user between base station network elements. Step 102: Partition the vertices of the weighted undirected graph based on edge weights to obtain multiple candidate partitioning schemes; Step 103: Divide the vertices of the weighted undirected graph based on the candidate partitioning scheme to obtain multiple groups, and calculate the variance of the vertex weights in all groups; Step 104: The candidate partitioning scheme corresponding to the minimum value among the multiple vertex weight variances is determined as the planning scheme for the centralized wireless access network.
[0027] This embodiment uses site traffic volume as node weights and the number of handover requests between sites as edge weights to form a quantifiable and computable weighted undirected graph. This method incorporates wireless network planning tasks such as site planning, C-RAN networking, handover link design, and transmission route design into the scope of graph theory computation, significantly improving the digital accuracy of wireless network planning. Furthermore, this implementation can generate planning schemes with high service cohesion within the C-RAN and low service coupling between C-RANs, fundamentally maximizing performance considerations in the planning scheme and greatly improving planning accuracy and efficiency.
[0028] For example, such as Figure 3 As shown, a weighted undirected graph G[V(weight n), E(weight m)], where V is a vertex of graph G (an independent network element), and E is the edge set of G (the transition between network elements), has a weight of n for a single vertex and a weight of m for a single edge, as shown in the figure. Figure 3 As shown.
[0029] The graph is generated by taking the wireless device network element (base station) as the vertex V; the base station network element traffic (GB) as the vertex weight n; the user handover between network elements as the edge E; and the number of handover requests between network elements as the edge weight m. The graph generated according to the above principles is a weighted directed graph of the base station set. It is simplified into a weighted undirected graph by bidirectional addition of handover data for the next step.
[0030] In some embodiments, the vertices of a weighted undirected graph are partitioned based on edge weights to obtain multiple candidate partitioning schemes; including: Step S1: Determine a vertex as a group; Step S2: Select a target vertex from any group, and merge the group containing the target vertex with the group containing the adjacent vertices of the target vertex to obtain multiple merged groups; Step S3: The optimal merged group is determined by ensuring that the total business volume of the merged group does not exceed a preset threshold and that the module degree increment of the merged group is the largest. Step S4: Based on the optimal merged grouping, determine the current multiple groups of the weighted undirected graph; Step S5: Determine the sum of the modularity of all current groups as the current Q value; Step S6: Determine whether the current Q value is greater than the previous Q value. If not, proceed to step S2; otherwise, proceed to step S7. Step S7: Determine the current partitioning methods of multiple groups as candidate partitioning schemes.
[0031] For example, the results of Louvain-based optimization of local wireless networks are as follows: Figure 4As shown, AF represents the station. Based on the modularity calculation results, the maximum overall Q value under the current combination is 10.034. If the merging continues, the Q value will decrease.
[0032] This embodiment searches for optimal planning (grouping) based on the Louvain algorithm, with the goal of maximizing modularity, while also considering the constraints of existing network base station / equipment room capacity on site grouping; based on the inter-site handover request data, it achieves maximum internal cohesion and minimum external coupling in C-RAN networking.
[0033] In some embodiments, the step of calculating the module degree increment of the merged group includes: The module degree increment of the merged group is calculated using the following formula. :
[0034] in, It is the sum of the edge weights within the merged group; It is the sum of the weights of the edges associated with the merged group; It is the sum of the weights of the edges connected to the target vertex i within the merged group; It is the sum of the weights of the edges connecting to the target vertex i; It is the sum of the weights of the edges in a weighted undirected graph.
[0035] In some embodiments, calculating the sum of the modularity of all current groups includes: The total modularity of all current groups is calculated using the following formula. ;
[0036] in, The number of groups, It is the sum of the edge weights within the group. It is the sum of the weights of the edges in the group association. It is the sum of the weights of the edges in a weighted undirected graph.
[0037] The goal of this C-RAN networking embodiment is to group adjacent sites with frequent interoperability handovers into one group as much as possible, so as to minimize interoperability between C-RAN services, while ensuring that the capacity of multiple C-RAN equipment rooms in the network is relatively balanced. In some embodiments, calculating the vertex weight variance for all groups includes: Calculate grouping The sum of the weights of the vertices ; The number of groups; Calculate the vertex weight variance for all groups. : .
[0038] Because Louvain optimization employs a greedy approach, the modularity Q of the output results for multiple calculations of a certain network region is roughly the same, but the local partitions may differ. Therefore, in this embodiment, Louvain is used to generate multiple partition results for a network region, and the result with better balance, i.e., the smallest vertex weight variance, is selected as the final C-RAN networking planning scheme.
[0039] Based on the same inventive concept, this application provides a centralized wireless access network planning device, see reference. Figure 5 As shown, the centralized wireless access network planning device 200 provided in this application embodiment includes at least: Establishment unit 201 is used to establish a weighted undirected graph with base station network elements as vertices and user handover between base station network elements as edges; wherein, the vertex weight is the service volume of the base station network element, and the edge weight is the number of handover requests by the user between base station network elements; The optimization unit 202 is used to partition the vertices of the weighted undirected graph based on the edge weights to obtain multiple candidate partitioning schemes; The computing unit 203 is used to partition the vertices of the weighted undirected graph based on the candidate partitioning scheme, obtain multiple groups, and calculate the variance of the vertex weights of all groups. The determining unit 204 is used to determine the candidate partitioning scheme corresponding to the minimum value among the multiple vertex weight variances as the planning scheme of the centralized wireless access network.
[0040] It should be noted that the principle of the centralized wireless access network planning device 200 provided in this application embodiment to solve the technical problem is similar to the method provided in this application embodiment. Therefore, the implementation of the centralized wireless access network planning device 200 provided in this application embodiment can refer to the implementation of the method provided in this application embodiment, and the repeated parts will not be described again.
[0041] Based on the same inventive concept, embodiments of this application also provide an electronic device, such as... Figure 6 As shown, it includes a memory and a processor. The memory stores an executable program, and the processor executes the executable program to implement the steps of the centralized wireless access network planning method provided in the above embodiments.
[0042] The aforementioned processor can be a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor, etc.
[0043] Since the electronic device described in this application embodiment is an electronic device equipped with a memory for implementing the centralized wireless access network planning method disclosed in this application embodiment, those skilled in the art can understand the structure and variations of the electronic device described in this application embodiment based on the centralized wireless access network planning method described in this application embodiment, and therefore will not be described again here.
[0044] This application also provides a computer-readable storage medium storing a computer program thereon. When the computer program is run by a processor, it implements the steps of the data flow behavior recognition method based on multi-source logs provided in the above embodiments.
[0045] The storage medium in this embodiment may be included in an electronic device; or it may exist independently and not be assembled into an electronic device. The storage medium carries one or more computer programs, which, when executed, implement the steps of the centralized wireless access network planning method provided in the above embodiments.
[0046] It should be understood that the various solutions in this embodiment have the same technical effects as those in the above method embodiments, and will not be repeated here.
[0047] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. Optionally, specific examples in this embodiment can refer to the examples described in any embodiment of this application, which will not be repeated here. Obviously, those skilled in the art should understand that the various modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular hardware and software combination.
[0048] This application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the centralized wireless access network planning method provided in the above embodiments.
[0049] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions targeted in the blocks may occur in a different order than those targeted in the drawings. For example, two consecutively represented blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0050] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. Multitasking and parallel processing may be advantageous in certain environments. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this application. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.
Claims
1. A centralized wireless access network planning method, characterized in that, include: A weighted undirected graph is constructed with base station network elements as vertices and user handover between base station network elements as edges; where the vertex weight is the traffic volume of the base station network element and the edge weight is the number of handover requests by the user between base station network elements. The vertices of the weighted undirected graph are partitioned based on edge weights, resulting in multiple candidate partitioning schemes; The vertices of the weighted undirected graph are divided into multiple groups based on the candidate partitioning scheme, and the variance of the vertex weights of all groups is calculated. The candidate partitioning scheme corresponding to the minimum value among the multiple vertex weight variances is determined as the planning scheme for the centralized wireless access network.
2. The method according to claim 1, characterized in that, Based on edge weights, the vertices of a weighted undirected graph are partitioned, resulting in multiple candidate partitioning schemes, including: Step S1: Determine a vertex as a group; Step S2: Select a target vertex from any group, and merge the group containing the target vertex with the group containing the adjacent vertices of the target vertex to obtain multiple merged groups; Step S3: The optimal merged group is determined by ensuring that the total business volume of the merged group does not exceed a preset threshold and that the module degree increment of the merged group is the largest. Step S4: Based on the optimal merged grouping, determine the current multiple groups of the weighted undirected graph; Step S5: Determine the sum of the modularity of all current groups as the current Q value; Step S6: Determine whether the current Q value is greater than the previous Q value. If not, proceed to step S2; otherwise, proceed to step S7. Step S7: Determine the current grouping methods as candidate planning schemes.
3. The method according to claim 2, characterized in that, The steps for calculating the module degree increment of the merged group include: The module degree increment of the merged group is calculated using the following formula. : in, It is the sum of the edge weights within the merged group; It is the sum of the weights of the edges associated with the merged group; It is the sum of the weights of the edges connected to the target vertex i within the merged group; It is the sum of the weights of the edges connecting to the target vertex i; It is the sum of the weights of the edges in a weighted undirected graph.
4. The method according to claim 2, characterized in that, Calculate the sum of the modularity of all current groups, including: The total modularity of all current groups is calculated using the following formula. ; in, The number of groups, It is the sum of the edge weights within the group. It is the sum of the weights of the edges in the grouped association. It is the sum of the weights of the edges in a weighted undirected graph.
5. The method according to claim 1, characterized in that, Calculate the variance of vertex weights for all groups, including: Calculate grouping The sum of the weights of the vertices ; The number of groups; Calculate the vertex weight variance for all groups. : 。 6. A centralized wireless access network planning device, characterized in that, include: A unit is established to construct a weighted undirected graph with base station network elements as vertices and user handover between base station network elements as edges; wherein, the vertex weight is the traffic volume of the base station network element, and the edge weight is the number of handover requests by the user between base station network elements. The optimization unit is used to partition the vertices of a weighted undirected graph based on edge weights, and obtain multiple candidate partitioning schemes. The computational unit is used to partition the vertices of the weighted undirected graph based on the candidate partitioning scheme, obtain multiple groups, and calculate the variance of the vertex weights of all groups. The determination unit is used to determine the candidate partitioning scheme corresponding to the minimum value among multiple vertex weight variances as the planning scheme for the centralized wireless access network.
7. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1-5.
8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method as described in any one of claims 1-5.
9. A computer program product, characterized in that, Includes a computer program / instruction that, when executed by a processor, implements the method as described in any one of claims 1-5.