1-Bit channel estimation and activity detection for intelligent reflecting surface-assisted multi-user millimeter wave MIMO systems

Intelligent reflecting surface (IRS)-assisted communication is a promising paradigm for the next-generation wireless systems. Existing channel estimation schemes for IRS-assisted systems employ orthogonal pilot sequences that effectively decouple a multi-user system into multiple single-user systems, and incur large spectral overhead and delay. In this paper, we consider a system where each IRS element is equipped with two 1-bit analog-to-digital converters (ADCs) that output the signs of the in-phase and the quadrature-phase components of the impinging signal. For such a system, we propose a novel channel estimation approach that simultaneously estimates the BS-IRS channel and UE-IRS channels with 1-bit received signals at the IRS. Specifically, we formulate channel estimation as a 1-bit compressed sensing (CS) problem using the inherent sparsity of the millimeter wave (mmWave) channel, and we propose a proximal group coordinate descent algorithm to solve the 1-bit CS problem, and a denoising algorithm to refine the channel estimate. We then extend our approach to an IRS-assisted system with massive number of users but sporadic activity, for joint user activity detection and channel estimation, based on the 1-bit received signals. Our proposed approach does not require orthogonal pilots and the pilot duration is independent of the number of users. Extensive simulation results are presented to demonstrate the effectiveness of our proposed approach to channel estimation and user activity detection in IRS-assisted systems.