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Accurate Beam Training for RIS-Assisted Wideband Terahertz Communication

Yuhao Chen, Jingbo Tan, Hao Mo, Richard MacKenzie, Linglong Dai

2023IEEE Transactions on Communications34 citationsDOI

Abstract

Terahertz (THz) communications have been widely considered as one of the promising technologies for future 6G wireless systems. In order to cope with the high path loss in THz systems, reconfigurable intelligent surface (RIS) composed of low-complexity reflecting elements can be deployed to generate directional beams. In order to acquire the direction of user equipment (UE) to send directional beams, the acquisition of accurate channel state information (CSI) is very important. Beam training is widely utilized to acquire the CSI. However, existing beam training schemes have not taken the wideband beam split effect into consideration, so the beam training accuracy decreases a lot in wideband scenarios. To solve this problem, in this paper, we propose an analytical beam training framework in RIS-assisted wideband THz communication systems. Specifically, we first propose a power distribution pattern (PDP) based direction estimation scheme, where the exact value of the received power is utilized to analytically calculate the UE direction. Then, we design the analytical codebook for the proposed framework based on the inherent parameters of the wideband THz system. Simulation results show that the proposed framework can achieve the near-optimal achievable rate performance with a lower beam training overhead than existing schemes.

Topics & Concepts

WidebandComputer scienceTerahertz radiationCodebookPath lossOverhead (engineering)Electronic engineeringChannel state informationBeam (structure)WirelessCommunications systemChannel (broadcasting)EngineeringTelecommunicationsOpticsArtificial intelligencePhysicsOperating systemAdvanced Wireless Communication TechnologiesMillimeter-Wave Propagation and ModelingIndoor and Outdoor Localization Technologies
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