Robust Design for Intelligent Reflecting Surface-Assisted MIMO-OFDMA Terahertz IoT Networks

Terahertz (THz) communication has been regarded as one promising technology to enhance the transmission capacity of future Internet-of-Things (IoT) users due its ultrawide bandwidth. Nonetheless, major obstacle that prevents actual deployment THz lies in inherent huge attenuation. Intelligent reflecting surface (IRS) and multiple-input-multiple-output (MIMO) represent two effective solutions for compensating large path loss systems. In this article, we consider an IRS-aided multiuser MIMO system with orthogonal frequency-division multiple (OFDM) access, where sparse radio frequency chain antenna structure is adopted reducing power consumption. The objective maximize weighted sum rate via jointly optimizing hybrid analog/digital beamforming at base station (BS) reflection matrix IRS. Since analog need cater all subcarriers, it difficult directly solve formulated problem, thus, alternatively iterative optimization algorithm proposed. Specifically, designed by solving a maximization while digital are both tackled using semidefinite relaxation (SDR) technique. Considering obtaining perfect channel state information (CSI) challenging task IRS-based systems, further explore case imperfect CSI channels from IRS users. Under setup, propose robust design scheme originally nonconvex problem. Finally, simulation results presented demonstrate effectiveness proposed algorithms.