Intelligent Reflecting Surface Aided MISO Uplink Communication Network: Feasibility and SINR Optimization.

In this paper we consider the signal-to-interference-and-noise ratio (SINR) optimization problem in the multi-user multi-input-single-output (MISO) uplink wireless network assisted by intelligent reflecting surface (IRS) under individual information rate constraints. We perform a comprehensive investigation on various aspects of this problem. First, under the individual rate constraints, we study its feasibility. We present a sufficient condition which guarantees arbitrary set of individual information rates. This result strengthens the feasibility condition in existing literature and is useful to the power control/energy efficiency (EE) maximization problem when IRS is present. Then, based on the penalty dual decomposition (PDD) and nonlinear equality alternative direction method of multipliers (neADMM) method, we present new algorithms to tackle the IRS configuration problems, which simultaneously involves multi-dimensional constant-modulus constraints and other additional constraints. Note that the similar hard-core problem has recurrently appeared in various research work on IRS recently. Convergence property and analytic solutions of our proposed algorithms are carefully examined. Moreover, iterative algorithms are developed to detect the feasibility and maximize the SINR. Extensive numerical results are presented to verify the effectiveness of our proposed algorithms.