Research on power allocation of integrated VLPC based on deep reinforcement learning - Shuai MA; Bing LI; Haihong SHENG; Rongyan GU; Hui ZHOU; Hongmei WANG; Yue WANG; Shiyin LI (Tongxin xuebao)
A power allocation scheme for integrated visible light position and communication (VLPC) system based on deep reinforcement learning was proposed to achieve power allocation for communication positioning integration.First, the frame structure design of integrated VLPC was proposed.Then the channel state information could be estimated by using the positioning information, and the CRLB of the positioning error was derived.Furthermore, the internal coupling relationship between positioning accuracy and communication rate was clarified.On this basis, a dynamic power allocation scheme based on deep deterministic policy gradient was proposed.Simulation results show that the proposed scheme can simultaneously achieve high-precision positioning and high-speed communication.