Reflection Resource Management for Intelligent Reflecting Surface Aided Wireless Networks

In this paper, the adoption of an intelligent reflecting surface (IRS) for multiple user pairs in two-hop networks is investigated. Different from existing studies on IRS that mainly focused tuning reflection coefficients all elements, we consider implementation true resource management (RRM) through identification best triggered module subset. More precisely, RRM builds premise our proposed modular structure consisting independent and controllable modules. context structure, investigate signal-to-interference-plus-noise ratio (SINR)-based max-min problem subject to per source terminals (STs) power budgets size constraint, via joint subset identification, transmit allocation, corresponding passive beamforming. Whereas NP-hard due which can be addressed by convex sparsity-inducing approximation hard constraint using mixed $\ell _{1,F}\text {-norm}$ , where it yields a suitable semidefinite relaxation. Using techniques separable programming, provide two-block alternating direction method multipliers (ADMM) algorithm approximated problem. Numerical simulations are used validate analysis assess performance as function system parameters. Further energy efficiency (EE) comparison demonstrates necessity meaningfulness introduced structure. Specifically, given network setting, there optimal value number modules system, when EE considered.