Deep Reinforcement Learning Based Transmission Scheme for UAV MIMO Communication

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Abstract
Unmanned Aerial Vehicle (UAV) massive MIMO has been considered an important technology in 6G communications. In this paper, we propose an efficient transmission scheme based on deep reinforcement learning (DRL) for the UAV massive MIMO. Specifically, the UAV 3D trajectory design, analog beam-forming and power allocation is designed to obtain a high spectral efficiency. We formulate the transmission design by a Markov decision process (MDP) framework, which is solved by the DRL based algrotihm. Considering that the action space is continuous, we use the deep deterministic policy gradient (DDPG) method to obtain the transmission scheme. The simulation results show that the proposed algorithm has a higher spectral efficiency than the previous algorithms.

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