An Enhanced Interference Alignment Strategy With MIL Criterion and RCG Algorithm for IRS-Assisted Multiuser MIMO

Abstract

An enhanced interference alignment strategy with minimum interference leakage (MIL) criterion and Riemannian conjugate gradient (RCG) algorithm is proposed for intelligent reflecting surface (IRS)-assisted multiuser multiple-input multiple-output (MIMO). In this letter, the maximum sum rate is formulated as the optimization objective, with alternate optimization of phase shift vector at IRS as well as precoding and interference suppression vectors at transceivers respectively. MIL interference alignment criterion is used to iteratively solve the precoding vector and the interference suppression vector via channel reciprocity property. RCG algorithm is further applied to derive the IRS phase shift vector and maximize sum rate with the condition of ensuring a given minimum interference leakage threshold to eliminate system interference. Simulation results reveal that the proposed strategy effectively enhances sum rate performance compared with the scheme using random IRS phase shift vector and random precoding/interference suppression vectors as well as “AP + RCG” scheme in IRS-assisted multiuser single-input single-output (SISO) scenario. In addition, compared with “MMSE + RCG” strategy in the case of same multi-antenna transceiver pairs and antenna numbers, the proposed strategy could make a tradeoff between sum rate performance and computational complexity.