论文标题
WPT辅助D2D通信的联合强大的横梁形式设计：分数编程和深度强化学习
Joint Robust Beamforming Design for WPT-assisted D2D Communications in MISO-NOMA: Fractional Programming and Deep Reinforcement Learning
论文作者
论文摘要
本文提出了一种计划的计划，该方案是针对第六代（6G）超质量机型通信（UMMTC）的计划。特别是，无线功率传输（WPT）辅助通信部署在非正交多访问（NOMA）下行链路网络中，以实现频谱和能源合作。本文侧重于稳健的波束形成设计，以最大程度地提高WPT辅助D2D通信在多输入单输出（MISO） - NOMA下行链路网络中的能源效率。为了有效解决公式的非符号能效性最大化问题，提出了纯部分编程（PFP）算法，其中通过分别应用Dinkelbach方法和Quadratic Transform，可以选择WPT设备的时间切换系数和基本站的光束成型向量。为了证明所提出算法的最佳性，提出了部分详尽的搜索算法作为基准。还采用了深入的增强学习（DRL）方法，以直接解决非cave问题。在存在不同的通道估计误差的情况下，比较了提出的PFP算法和基于DDPG的算法。仿真结果表明，如果可以获得完美的通道状态信息（CSI），则提出的PFP算法优于基于DDPG的算法，或者仅具有较小的误差，而基于DDPG的算法则在通道估计准确性不满意时更强大。另一方面，可以得出结论，NOMA方案可以比OMA在传统多用户下行网络中WPT辅助D2D通信的能源效率上提供更高的增益。
This paper proposes a scheme for the envisioned sixth-generation (6G) ultra-massive Machine Type Communications(umMTC). In particular, wireless power transfer (WPT) assisted communication is deployed in non-orthogonal multiple access (NOMA) downlink networks to realize spectrum and energy cooperation. This paper focuses on joint robust beamforming design to maximize the energy efficiency of WPT-assisted D2D communications in multiple-input single-output (MISO)-NOMA downlink networks. To efficiently address the formulated non-concave energy efficiency maximization problem, a pure fractional programming (PFP) algorithm is proposed, where the time switching coefficient of the WPT device and the beamforming vectors of the base station are alternatively optimized by applying the Dinkelbach method and quadratic transform respectively. To prove the optimality of the proposed algorithm, the partial exhaustive search algorithm is proposed as a benchmark. A deep reinforcement learning (DRL)-based method is also applied to directly solve the non-concave problem. The proposed PFP algorithm and the DDPG-based algorithm are compared in the presence of different channel estimation errors. Simulation results show that the proposed PFP algorithm outperforms the DDPG-based algorithm if perfect channel state information (CSI) can be obtained or just have minor errors, while the DDPG-based algorithm is more robust when the channel estimation accuracy is unsatisfactory. On the other hand, one can conclude that the NOMA scheme can provide a higher gain than OMA on the energy efficiency of the WPT-assisted D2D communication in legacy multi-user downlink networks.
