Characterization of IRS-aided Indoor Wireless Virtual-Reality with Hybrid Beamforming

Abstract

This paper introduces an optimum solution for a utility function that increases spectral efficiency in wireless Virtual Reality (VR) systems. This system uses Multi-user Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MU-MIMO OFDM) with hybrid beamforming in indoor Intelligent Reflecting Surface (IRS) based Downlink (DL) scenario. Given the critical need to maximize the rate for transmitting VR traffic to meet the low-latency requirements, a substantial bandwidth allocation is essential. This bandwidth is assumed to be in the mmWave band, according to the IEEE 802.11ad/ay standard. The proposed utility function takes into account various delays, including processing, transmission and queuing delays, on both DL and Uplink (UL). Moreover, the relation between transmission delay and the utility function is examined in different Signal-to-Noise Ratio (SNR) levels, using both mean and minimum channel gain metrics. An optimization approach is applied to iteratively determine the IRS phase shifts and effective channel gain. The simulation results are benchmarked against NS3 simulations, showing a high degree of consistency. With an average accuracy of 81.57% the calculated DL and UL rates match the NS3 results when considering the IRS. Also, our proposed method achieves superior performance in the case of complexity over the existing designs.