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您的检索式：作者名="DENG Danhao"
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| 1 | Trajectory Optimization and Power Allocation Scheme Based on DRL in Energy Efficient UAV-Aided Communication Networks显示文摘With flexibility, convenience and mobility, unmanned aerial vehicles(UAVS) can provide wireless communication networks with lower costs, easier deployment, higher network scalability and larger coverage.This paper proposes the deep deterministic policy gradient algorithm to jointly optimize the power allocation and flight trajectory of UAV with constrained effective energy to maximize the downlink throughput to ground users. To validate the proposed algorithm, we compare with the random algorithm, Q-learning algorithm and deep Q network algorithm. The simulation results show that the proposed algorithm can effectively improve the communication quality and significantly extend the service time of UAV. In addition, the downlink throughput increases with the number of ground users. | WANG Chaowei CUI Yuling DENG Danhao WANG Weidong JIANG Fan | 2022 | Chinese Journal of Electronics2022，31，3： | 1 |
| 2 | Joint Flexible Duplexing and Power Allocation with Deep Reinforcement Learning in Cell-Free Massive MIMO System显示文摘Network-assisted full duplex(NAFD)cellfree(CF)massive MIMO has drawn increasing attention in 6G evolvement.In this paper,we build an NAFD CF system in which the users and access points(APs)can flexibly select their duplex modes to increase the link spectral efficiency.Then we formulate a joint flexible duplexing and power allocation problem to balance the user fairness and system spectral efficiency.We further transform the problem into a probability optimization to accommodate the shortterm communications.In contrast with the instant performance optimization,the probability optimization belongs to a sequential decision making problem,and thus we reformulate it as a Markov Decision Process(MDP).We utilizes deep reinforcement learning(DRL)algorithm to search the solution from a large state-action space,and propose an asynchronous advantage actor-critic(A3C)-based scheme to reduce the chance of converging to the suboptimal policy.Simulation results demonstrate that the A3C-based scheme is superior to the baseline schemes in term of the complexity,accumulated log spectral efficiency,and stability. | Danhao Deng Chaowei Wang Zhi Zhang Lihua Li Weidong Wang | 2023 | China Communications2023，20，4： | 0 |
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