5G基站自适应天馈系统设计与建模

为了提供一个各方面更优的全自动天面自适应调整方案,在降低维护成本的同时实现更优覆盖效果,从5G天面的信号辐射方向调整方法入手,对5G基站自适应天馈系统的智能调节系统设计关键技术进行研究,提出对基于深度强化学习的基站天面自适应调节策略。基于此设计了5G基站自适应天馈系统,可以使用电信公司RSRP信号覆盖地图作为数据源,获取当前状态的观测值并自动分析数据,对天面进行自动调整。在虚拟环境下,对基于强化学习的系统进行了模拟搭建与仿真训练,结果符合预期。

Design and modeling of 5G base station adaptive antenna feed system

To provide a fully automatic antenna adaptive adjustment scheme with advantages of better performance, wider coverage and lower maintenance cost, the key design technologies of intelligent adjustment system of adaptive antenna feed system of 5g-based station are studied from the perspective of signal radiation direction adjustment of antenna panel. An adaptive adjustment strategy for base-station antenna based on deep reinforcement learning is proposed. The adaptive antenna feed system designed with the proposed strategy can use telecom RSRP coverage map as a data source, and obtain the current state of the observed values to automatically analyze data and adjust the antenna panels. In a virtual environment, the system based on reinforcement learning is simulated and trained, and the results are in line with expectations.