Performance Tradeoff of RIS Beam Training: Overhead vs. Achievable SNR - Laue, Friedemann; Garkisch, Moritz; Jamali, Vahid; Schober, Robert (Conference Record - Asilomar Conference on Signals, Systems and Computers, 2022)
In this paper, we consider large reconfigurable intelligent surfaces (RISs) for millimeter-wave (mmWave) communication systems and study the tradeoff between the overhead of RIS beam training and the achievable signal-to-noise ratio (SNR). More specifically, we analyze the overhead of codebook-based RIS configuration for three popular training strategies. Furthermore, we derive scaling laws for the achievable SNR and highlight their differences for small and large RIS codebooks. Our numerical simulations show that low-overhead training strategies are essential to maintain high system performance.
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