In this study, the authors propose a simultaneous wireless information and power transfer scheme based on the power-splitting (PS) protocol for a massive multiple-input multiple-output (MIMO) network. On the downlink, the base station transmits the information and energy simultaneously to each terminal and each terminal divides the received signals by its PS device between information decoder and energy harvester (EH). On the uplink, a portion of the energy harvested by EH is drawn for uplink pilot transmission in the coming frame and then the other is used for uplink data transmission in the current frame. Based on this scheme, the closed-form lower bound expressions are obtained for the achievable downlink rate and uplink rate of each terminal and then are utilised to formulate an optimisation problem that is to maximise achievable sum rate of the whole network while ensuring the minimum required uplink and downlink rates of each terminal. However, as the original optimisation problem is non-convex and non-linear and very hard to solve directly, an algorithm is proposed by utilising successive approximation method based on geometric program. Numerical results verify the correctness and feasibility of the proposed algorithm.

中文翻译：

---

大规模MIMO网络的同时无线信息和功率传输

在这项研究中，作者针对大规模多输入多输出（MIMO）网络提出了一种基于功率分配（PS）协议的同时无线信息和功率传输方案。在下行链路上，基站将信息和能量同时发送到每个终端，并且每个终端通过其PS设备在信息解码器和能量收集器（EH）之间划分接收到的信号。在上行链路上，EH收集的能量的一部分被提取以用于下一帧中的上行链路导频传输，然后将另一部分用于当前帧中的上行链路数据传输。基于此方案，针对每个终端可实现的下行速率和上行速率获得封闭形式的下界表达式，然后将其用于表述一个优化问题，该优化问题将在确保最小的所需上下行速率的同时最大化整个网络的可实现总速率。每个终端。然而，由于最初的优化问题是非凸和非线性的，并且很难直接求解，因此提出了一种基于几何程序的逐次逼近方法。数值结果验证了所提算法的正确性和可行性。提出了一种基于几何程序的逐次逼近算法。数值结果验证了所提算法的正确性和可行性。提出了一种基于几何程序的逐次逼近算法。数值结果验证了所提算法的正确性和可行性。