基于智能反射面的无线携能认知网络鲁棒传输设计

Design of the wireless powered cognitive radio network based on intelligent reflecting surfaces

针对智能反射面辅助的无线携能认知网络,提出了一种基于用户非完美信道状态信息的波束成形方案,提高网络的频谱和能量收集效率。在假设用户信道误差范数有界的条件下,建立了以信息接收用户最小可达速率最大化为目标函数,以满足信息接收用户和能量接收用户需求、主用户干扰阈值和基站最大发射功率为约束条件的优化问题。针对此非凸问题,提出利用三角不等式、交替方向乘子法和交替优化的迭代算法,以较低的计算复杂度求解得到基站的有源波束成形权矢量和智能反射面的无源波束成形矩阵。最后,仿真验证了所提方案相较于随机相位方案能够有效提高系统的性能,证明了在携能认知网络中引入智能反射面的可行性和有效性。

This paper proposes a beamforming(BF)scheme based on imperfect channel state information(CSI)to improve the spectrum and energy harvesting efficiency for an intelligent reflecting surface(IRS)assisted wireless powered cognitive radio network.Assuming that only the imperfect CSI is available,first,we formulate a constrained problem to maximize the minimum achievable rate among information receivers(IRs),while satisfying requirements of IRs and energy receivers(ERs),interference threshold of primary users and transmit power budget of base station.Second,we propose a low computational-complexity algorithm that adopts the triangle inequality,the alternating direction method of multipliers and the alternating optimization to obtain the active and passive beamformers for base station as well as IRS.Finally,computation simulations demonstrate that the proposed scheme can effectively improve the system performance,verifying the feasibility and effectiveness of introducing IRS into the wireless powered cognitive radio network.