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（RIS）赋能的底层设备到设备（D2D）通信系统。考虑瑞利衰落信道以及直连与RIS增强D2D信道同时存在的一般情况，本文给出了D2D通信链路中断概率（OP）的闭式表达式。随后，针对所考虑的RIS赋能底层D2D系统，我们构建了一个中断概率最小化问题。在两种RIS部署拓扑结构下，以D2D源端发射功率和蜂窝用户所受有限干扰为约束条件，我们旨在联合优化D2D源端发射功率与RIS位置。由于优化变量相互耦合，所构建的优化问题极其棘手。我们提出了一种可解析求解的等效变换。在变换后的问题中，我们推导出D2D接收端信干噪比（SINR）平均值的闭式表达式。通过仿真结果验证了理论推导的正确性，并得出了多种系统设计启示。研究表明，所提出的RIS赋能底层D2D系统设计方案优于基准的半自适应最优功率与最优距离方案，分别实现了44%和20%的性能提升。