摘要
随着网优智能优化的推进,各类算法不断演进更新,需要真实网络进行大量试点验证。重保区域是重点保障区域,出现覆盖问题无法进行多次参数调整试验结果。本文通过强化学习算法模拟重保小区的参数调整对网络的影响,快速获取参数调整优化效果,提供最佳参数优化方案,有效提升网络质量。
With the advancement of network optimization methods,various algorithms are constantly evolving and updating,which need a large number of test on the real network to verify.However,the key areas are impossible to adjust the test results in the real network.In this paper,reinforcement learning is used to simulate the impact of parameter adjustment on the network,so as to quickly obtain the optimization eff ect and provide the best parameter optimization scheme,which can eff ectively improve the quality of the network.
作者
程楠
王西点
石铎
CHENG Nan;WANG Xi-dian;SHI Duo(China Mobile Group Design Institute Co.,Ltd.,Beijing 100080,China)
出处
《电信工程技术与标准化》
2024年第3期26-30,共5页
Telecom Engineering Technics and Standardization
关键词
强化学习
重保场景
网优
reinforcement Learning
key area
network optimization
