Double-Active-IRS Aided Wireless Communication: Deployment Optimization and Capacity Scaling
Zhenyu Kang, Changsheng You, Rui Zhang
Abstract
In this letter, we consider a double-active-intelligent reflecting surface (IRS) aided wireless communication system, where two active IRSs assist the communication from a base station (BS) to multiple users via double-reflection links. Under the assumption of fixed per-element amplification power for each active-IRS element, we formulate a rate maximization problem subject to practical constraints on the reflection design, elements allocation, and placement of active IRSs. To solve this non-convex problem, we first obtain the optimal active-IRS reflections and BS beamforming, based on which we then jointly optimize the active-IRS elements allocation and placement by using the alternating optimization (AO) method. Moreover, we show that given the fixed per-element amplification power, the received signal-to-noise ratio (SNR) at the user increases asymptotically with the square of the number of reflecting elements; while given the fixed number of reflecting elements, the SNR does not increase with the per-element amplification power when it is asymptotically large. Finally, numerical results validate the proposed algorithm and compare the rate performance to benchmark systems.