基于超密集组网的无线传输容量优化方法研究  

Research on Optimization Methods for Wireless Transmission Capacity Based on Ultra-Dense Network

作　　者：吴炼 WU Lian(Diqing Branch of China Mobile Communications Group Yunnan Co.,Ltd.,Diqing 674499,China)

机构地区：[1]中国移动通信集团云南有限公司迪庆分公司,云南迪庆674499

出　　处：《数字通信世界》2025年第3期4-6,共3页Digital Communication World

摘　　要：超密集组网(UDN)是5G/6G网络扩容关键技术,但微基站密度大幅提升导致跨层干扰。鉴于此本文提出了优化方法:利用分布式探针采集参数,改进支持向量机识别容量瓶颈,构建深度强化学习自适应模型优化资源。实验表明,该方案有效提升了吞吐量和频谱效率,相较于传统方法具有明显优势。Ultra-Dense Network(UDN)is a key technology for capacity expansion in 5G/6G.However,the increase in the density of micro base stations leads to cross-layer interference.This paper proposes optimization methods:using distributed probes to collect parameters,improving the Support Vector Machine to identify capacity bottlenecks,and constructing a deep reinforcement learning adaptive model to optimize resources.Experiments show that this scheme effectively improves throughput and spectral efficiency and has obvious advantages compared with traditional methods.

关 键 词：超密集组网 无线传输容量 支持向量机 优化方法 

分 类 号：TN929.5[电子电信—通信与信息系统]