基于粒子群优化算法的5G波束权值寻优方法

王建斌; 王恒钧; 吴松; 王贞凯

doi:10.11959/j.issn.1000-0801.2023146

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基于粒子群优化算法的5G波束权值寻优方法

研究与开发 | 更新时间：2024-06-05

- 基于粒子群优化算法的5G波束权值寻优方法
- 5G beamforming weight optimization method based on particle swarm optimization algorithm
- 电信科学 2023年39卷第7期页码：23-34
- 作者机构：
  
  1. 浙江大学，浙江杭州 310027
  2. 中国电信股份有限公司浙江分公司，浙江杭州 310005
- 作者简介：
  
  [ "王建斌（1977- ），男，浙江大学博士生，中国电信股份有限公司浙江分公司无线网络中心主任、正高级工程师，主要从事无线网络新技术、新产品的研究以及无线网络的规划、优化等工作" ]
  [ "王恒钧（1971- ），男，中国电信股份有限公司浙江分公司云网发展部（科技创新部）总经理、高级工程师，主要从事云网技术及规划、工程管理等工作" ]
  [ "吴松（1987- ），男，中国电信股份有限公司浙江分公司高级工程师，主要从事无线网系统分析优化，5G网络规划、优化和课题研究工作" ]
  [ "王贞凯（1973- ），男，中国电信股份有限公司浙江分公司高级工程师，主要研究方向为无线网络新技术、新产品以及无线网络的规划及工程管理等" ]
- 基金信息：
  
  浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province(LZ23D060003)
- DOI：10.11959/j.issn.1000-0801.2023146
  中图分类号： TN929.5
- 网络出版日期：2023-07，
  
  纸质出版日期：2023-07-20
- 稿件说明：
移动端阅览
王建斌, 王恒钧, 吴松, 等. 基于粒子群优化算法的5G波束权值寻优方法[J]. 电信科学, 2023,39(7):23-34.

Jianbin WANG, Hengjun WANG, Song WU, et al. 5G beamforming weight optimization method based on particle swarm optimization algorithm[J]. Telecommunications science, 2023, 39(7): 23-34.
王建斌, 王恒钧, 吴松, 等. 基于粒子群优化算法的5G波束权值寻优方法[J]. 电信科学, 2023,39(7):23-34. DOI： 10.11959/j.issn.1000-0801.2023146.

Jianbin WANG, Hengjun WANG, Song WU, et al. 5G beamforming weight optimization method based on particle swarm optimization algorithm[J]. Telecommunications science, 2023, 39(7): 23-34. DOI： 10.11959/j.issn.1000-0801.2023146.

摘要

为解决高层建筑物室内5G信号覆盖不足、优化难度大的问题，提出基于粒子群优化（particle swarm optimization，PSO）算法的5G波束权值寻优方法。通过采集终端数据将网络解耦成多个子网切片，对单小区权值库进行规划和仿真，构建多小区权值组变量以及适应度函数。最后，采用PSO算法求解多小区波束权值组局部最优值。测试结果表明，平均参考信号接收功率（reference signal receiving power，RSRP）提升8.7%，平均信干噪比（signal to interference plus noise ratio，SINR）提升17.5%，下行速率提升27.3%。所提方法在5G天线波束权值寻优上具有低成本、高效率、智能化的优势，可以改善高层室内用户的感知。

Abstract

In order to solve the problems of insufficient indoor 5G signal coverage and difficulty in optimization of high-rise buildings

the 5G beamforming weight optimization method based on particle swarm optimization (PSO) algorithm was proposed.Decoupling and reducing the network dimension into multiple subnet slices by collecting the data reported by the terminal

and the single cell weight database was planned and simulated to create the multi-cells weights group and fitness function.Finally

the PSO algorithm was adopted to obtain the local optimal weight group of the multi-cells.The test results show that the reference signal receiving power (RSRP) is improved by 8.7%

the signal to interference plus noise ratio (SINR) is improved by 17.5%

the downlink throughput is promoted by 27.3% together.The proposed method has the advantages of low cost

high efficiency and intelligence

and can significantly improve the user perception in high-rise buildings.

关键词

Keywords

references

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