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We focus on the realistic maximization of the uplink minimumsignal-to-interference-plus-noise ratio (SINR) of a general multiple-inputsingle-output (MISO) system assisted by an intelligent reflecting surface (IRS)in the large system limit accounting for HIs. In particular, we introduce theHIs at both the IRS (IRS-HIs) and the transceiver HIs (AT-HIs), usuallyneglected despite their inevitable impact. Specifically, the deterministicequivalent analysis enables the derivation of the asymptotic weightedmaximum-minimum SINR with HIs by jointly optimizing the HIs-aware receiver, thetransmit power, and the reflect beamforming matrix (RBM). Notably, we obtainthe optimal power allocation and reflect beamforming matrix with low overheadinstead of their frequent necessary computation in conventional MIMO systemsbased on the instantaneous channel information. Monte Carlo simulations verifythe analytical results which show the insightful interplay among the keyparameters and the degradation of the performance due to HIs.

Asymptotic Analysis of Max-Min Weighted SINR for IRS-Assisted MISO Systems with Hardware Impairments