Asymptotic analysis of max-min weighted SINR for IRS-assisted MISO aystems with hardware impairments

Abstract

We focus on the realistic maximization of the uplink minimum signal-to-interference-plus-noise ratio (SINR) of a general multiple-input single-output (MISO) system assisted by an intelligent reflecting surface (IRS) in the large system limit accounting for HIs hardware impairments (HIs). In particular, we introduce the HIs at both the IRS (IRS-HIs) and the additive transceiver HIs (AT-HIs), usually neglected despite their inevitable impact. Specifically, the deterministic equivalent analysis enables the derivation of the asymptotic weighted maximum-minimum SINR with HIs by jointly optimizing the HIs-aware receiver, the transmit power, and the reflecting beamforming matrix (RBM). Notably, we obtain the optimal power allocation and reflecting beamforming matrix with low overhead instead of their frequent necessary computation in IRS-assisted MIMO systems based on the instantaneous channel information. Monte Carlo simulations verify the analytical results which show the insightful interplay among the key parameters and the degradation of the performance due to HIs.