Intelligent Reflecting Surface Aided MISO Uplink Communication Network: Feasibility and Power Minimization for Perfect and Imperfect CSI

TL;DR

This paper investigates power minimization in IRS-assisted MISO uplink networks under QoS constraints, proposing new feasibility conditions and algorithms for perfect and imperfect CSI scenarios, validated by extensive simulations.

Contribution

It introduces a new feasibility condition for high transmit power scenarios and develops novel algorithms for power minimization with perfect and imperfect CSI.

Findings

Proposed algorithms effectively minimize power while satisfying QoS.

New feasibility condition extends existing literature.

Algorithms perform well under imperfect CSI conditions.

Abstract

In this paper, we consider the weighted sum-power minimization under quality-of-service (QoS) constraints in the multi-user multi-input-single-output (MISO) uplink wireless network assisted by intelligent reflecting surface (IRS). We perform a comprehensive investigation on various aspects of this problem. First, when users have sufficient transmit powers, we present a new sufficient condition guaranteeing arbitrary information rate constraints. This result strengthens the feasibility condition in existing literature. Then, we design novel penalty dual decomposition (PDD) based and nonlinear equality constrained alternative direction method of multipliers (neADMM) based solutions to tackle the IRS-dependent-QoS-constraints, which effectively solve the feasibility check and power minimization problems. Besides, we further extend our proposals to the cases where channel status information (CSI) is imperfect and develop an online stochastic algorithm that satisfy QoS constraints stochastically without requiring prior knowledge of CSI errors. Extensive numerical results are presented to verify the effectiveness of our proposed algorithms.