反向散射辅助无线供电D2D网络中的鲁棒能效优化

为了提高反向散射辅助无线供电中设备对设备（device-to-device，D2D）的网络能效（energy efficiency，EE）和系统的鲁棒性，研究了在具有信道不确定性的反向散射辅助无线供电D2D网络中的鲁棒能效资源分配问题。在功率站最大发射功率、所需服务质量和能耗约束下，通过联合优化发射功率、传输时间和反射系数使所有D2D用户的总EE最大化；利用一个次优解的迭代鲁棒算法解决了提出问题的非凸性。仿真结果表明，提出的算法具有收敛性及对不确定信道的鲁棒性。

Robust energy efficiency optimization in backscatter-aided wireless-powered D2D networks

To improve the energy efficiency (EE) and system robustness of backscatter-assisted wireless-powered device-to-device (D2D) network, we investigate the problem of robust EE resource allocation in this network with channel uncertainties. Under the constraints of maximum transmit power of the power station, required quality of service and energy consumption, the total EE of all D2D users is maximized by jointly optimizing the transmit power, transmission time, and reflection coefficient. The non-convexity of the proposed problem is solved using an iterative robust algorithm with sub-optimal solutions. Simulation results show the convergence of the proposed algorithm and robustness to uncertain channels.