This study investigates the outage performance of an under-laying wireless-powered secondary system that reuses the primary users (PU) spectrum in a multiple-input multiple-output (MIMO) cognitive radio (CR) network. Each secondary user (SU) harvests energy and receives information simultaneously by applying power splitting (PS) protocol. The communication between SUs is aided by a two-way (TW) decode and forward (DF) relay. We formulate a problem to design the PS ratios at SUs, the power control factor at the secondary relay, and beamforming matrices at all nodes to minimize the secondary network's outage probability. To address this problem, we propose a two-step solution. The first step establishes closedform expressions for the PS ratios at each SU and secondary relay's power control factor. Furthermore, in the second step, interference alignment (IA) is used to design proper precoding and decoding matrices for managing the interference between secondary and primary networks. We choose IA matrices based on the minimum mean square error (MMSE) iterative algorithm. The simulation results demonstrate a significant decrease in the outage probability for the proposed scheme compared to the benchmark schemes, with an average reduction of more than two orders of magnitude achieved.

翻译：本研究探讨了在多输入多输出（MIMO）认知无线电（CR）网络中，复用主用户（PU）频谱的底层无线供电次级系统的中断性能。每个次级用户（SU）通过采用功率分割（PS）协议同时进行能量收集和信息接收。SU之间的通信由双向（TW）译码转发（DF）中继辅助完成。我们构造了一个优化问题，以设计SU处的PS比值、次级中继的功率控制因子以及所有节点的波束赋形矩阵，从而最小化次级网络的中断概率。为解决该问题，我们提出了一种两步解法：第一步推导了每个SU的PS比值和中继功率控制因子的闭式表达式；第二步采用干扰对齐（IA）技术设计合适的预编码和解码矩阵，以管理次级网络与主网络之间的干扰。IA矩阵基于最小均方误差（MMSE）迭代算法选取。仿真结果表明，与基准方案相比，所提方案的中断概率显著降低，平均降幅超过两个数量级。