Joint Power Allocation and Reflecting-Element Activation for Energy Efficiency Maximization in IRS-Aided Communications Under CSI Uncertainty

We study the joint power allocation and reflecting element (RE) activation to maximize the energy efficiency (EE) in communication systems assisted by an intelligent reflecting surface (IRS), taking into account imperfections in channel state information (CSI). The robust optimization problem is mixed integer, i.e., the optimization variables are continuous (transmit power) and discrete (binary states of REs). In order to solve this challenging problem we develop two algorithms. The first one is an alternating optimization (AO) method that attains a suboptimal solution with low complexity, based on the Lambert W function and a dynamic programming (DP) algorithm. The second one is a branch-and-bound (B&B) method that uses AO as its subroutine and is formally guaranteed to achieve a globally optimal solution. Both algorithms do not require any external optimization solver for their implementation. Furthermore, numerical results show that the proposed algorithms outperform the baseline schemes, AO achieves near-optimal performance in most cases, and B&B has low computational complexity on average.

💡 Research Summary

This paper addresses the problem of maximizing the worst‑case energy efficiency (EE) of an intelligent reflecting surface (IRS)‑assisted single‑antenna link under channel state information (CSI) uncertainty. The authors model the actual channel as the sum of an estimated component and an unknown error bounded in Euclidean norm by a radius ξ, which captures deterministic CSI errors. The IRS consists of N reflecting elements (REs) that can be switched on or off (binary variables) while their phase shifts are set to align the estimated direct and reflected paths.

The worst‑case signal‑to‑noise ratio (SNR) is expressed as
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