In this paper, we study underlay device-to-device (D2D) communication systems empowered by a reconfigurable intelligent surface (RIS) for cognitive cellular networks. Considering Rayleigh fading channels and the general case where there exist both the direct and RIS-enabled D2D channels, the outage probability (OP) of the D2D communication link is presented in closed-form. Next, for the considered RIS-empowered underlaid D2D system, we frame an OP minimization problem. We target the joint optimization of the transmit power at the D2D source and the RIS placement, under constraints on the transmit power at the D2D source and on the limited interference imposed on the cellular user for two RIS deployment topologies. Due to the coupled optimization variables, the formulated optimization problem is extremely intractable. We propose an equivalent transformation which we are able to solve analytically. In the transformed problem, an expression for the average value of the signal-to-interference-noise ratio (SINR) at the D2D receiver is derived in closed-form. Our theoretical derivations are corroborated through simulation results, and various system design insights are deduced. It is indicatively showcased that the proposed RIS-empowered underlaid D2D system design outperforms the benchmark semi-adaptive optimal power and optimal distance schemes, offering $44\%$ and $20\%$ performance improvement, respectively.

翻译：本文研究了认知蜂窝网络中由可重构智能表面赋能底层设备到设备通信系统。考虑瑞利衰落信道及直连链路与RIS辅助D2D链路共存的通用场景，推导了D2D通信链路中断概率的闭式表达式。针对所考虑的RIS赋能底层D2D系统，构建了中断概率最小化问题。在D2D源端发射功率约束及对蜂窝用户有限干扰约束下，针对两种RIS部署拓扑结构，提出D2D源端发射功率与RIS部署位置的联合优化方案。由于优化变量耦合，所构建的优化问题极其棘手。本文提出一种可解析求解的等价变换方法。在变换后的优化问题中，推导了D2D接收端信号-干扰-噪声比均值的闭式表达式。通过仿真验证理论推导的正确性，并总结出多种系统设计启示。结果表明，所提出的RIS赋能底层D2D系统设计方案显著优于基准的半自适应功率最优方案和距离最优方案，分别带来44%和20%的性能提升。