Standalone-Intelligent Reflecting Surface Control Method Using Hierarchical Exploration by Beamwidth Expansion and Environment-Adaptive Codebook

Abstract

Intelligent reflecting surfaces (IRS) have garnered attention for the high-capacity and reliable communication required by Beyond 5G. However, IRS control in existing studies assumes information sharing and control instructions from base stations (BSs), thus requiring a backhaul link to the core network and BSs. This requires the construction of a network system, ruining the advantages of IRS, such as its low cost and installation flexibility. Therefore, a standalone-IRS, which is completely independent of the core network and BSs, is expected to maximize the performance of the IRS. However, a standalone-IRS cannot obtain sufficient information for control decisions, such as channel state information, which is frequently used in existing studies; therefore, inefficient control methods, such as exploration, must be used. To this end, this study proposes a significant reduction in the overhead required for exploration by hierarchical exploration and a reduction in the exploration itself using codebooks to store the results of exploration. Furthermore, to prevent the degradation of communication quality due to the use of hierarchical exploration and codebooks, we propose an effective beamwidth expansion method for hierarchical exploration and an efficient codebook construction method based on user distribution as elemental methods. In this study, we evaluated the overhead reduction and communication quality of the standalone-IRS control by combining these methods through simulations.