Intelligent reflecting surfaces (IRSs) have emerged as a promising wireless technology for the dynamic configuration and control of electromagnetic waves, thus creating a smart (programmable) radio environment. In this context, we study a multi-IRS assisted two-way communication system consisting of two users that employ full-duplex (FD) technology. More specifically, we deal with the joint IRS location and size (i.e., the number of reflecting elements) optimization in order to minimize an upper bound of system outage probability under various constraints, namely, minimum and maximum number of reflecting elements per IRS, maximum number of installed IRSs, maximum total number of reflecting elements (implicit bound on the signaling overhead) as well as maximum total IRS installation cost. First, the problem is formulated as a discrete optimization problem and, then, a theoretical proof of its NP-hardness is given. Moreover, we provide a lower bound on the optimum value by solving a linear-programming relaxation (LPR) problem. Subsequently, we design two polynomial-time algorithms, a deterministic greedy algorithm and a randomized approximation algorithm, based on the LPR solution. The former is a heuristic method that always computes a feasible solution for which (a posteriori) performance guarantee can be provided. The latter achieves an approximate solution, using randomized rounding, with provable (a priori) probabilistic guarantees on the performance. Furthermore, extensive numerical simulations demonstrate the superiority of the proposed algorithms compared to the baseline schemes. Finally, useful conclusions regarding the comparison between FD and conventional half-duplex (HD) systems are also drawn.
翻译:智能反射表面(IRS)已经成为一种有希望的动态配置和控制电磁波的无线技术,成为动态配置和控制电磁波的无线技术,从而创造一个智能(可编程)无线电环境。在这方面,我们研究一个由使用全态(FD)技术的两个用户组成的多IRS辅助双向通信系统。更具体地说,我们处理IRS的联合位置和大小(即反映元素的数量)优化,以便最大限度地减少在各种制约下系统超值的可能性,这些制约包括:反映电磁波要素的最小和最大数量,安装的IRS的最大数量,反映要素的最大总数(信号间接约束在信号管理上)以及IRS安装费用的最大总额。首先,这一问题是作为一个离散的优化问题提出来,然后提供其NP-硬度的理论证明。此外,我们通过解决一个可编程简化的宽松(LPR)问题,我们设计两个多边-时间算法,一个确定性稳度的内含度的定量算法,以及一个最终的精确性算法,它以Larial 提供一种稳定性前的精确性计算方法。