An Efficient Beam Searching in Hybrid Intelligent Reflecting/Refracting Surfaces (IRS)-Aided mmWave 6G Network
Shikhar Verma, Yuichi Kawamoto, Nei Kato, Takahiro Saiwai, Masamichi Yonehara
Abstract
Hybrid Intelligent Reflecting/Refracting Surfaces (HIRS) offer a promising solution to the limitations faced by Intelligent Reflecting Surfaces (IRS) in high-frequency bands, owing to their versatile utilization of reflective and refractive techniques across indoor and outdoor surfaces. This paper investigates a hierarchical beam-sweeping (HBS) approach tailored for HIRS-assisted millimeter-wave networks, aiming to pinpoint user locations with reduced overhead. However, the HBS method typically entails numerous coarse steps for user identification, primarily due to its initial exploration starting with broader beam widths at the lowest detectable signal-to-noise ratio (SNR), gradually narrowing down with increasing SNR. Such a process raises concerns about inadequate time for user discovery within HIRS coverage and available maximum beam search time. To mitigate this, we propose a novel method to optimize beam width allocation at the outset of beam searching, prioritizing maximum SNR for all users in the initial step to avoid multiple steps of HBS. Through extensive simulations and analyses across varied indoor and outdoor environments, encompassing diverse user counts and coverage distances, we demonstrate the efficacy of our proposed approach in enhancing network performance. By dynamically adjusting beam widths, our method adeptly accommodates the requirements of diverse indoor and outdoor environments within the allocated maximum beam searching time.