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In this paper, we propose an reconfigurable intelligent surface (RIS)enhanced spectrum sensing system, in which the primary transmitter is equippedwith single antenna, the secondary transmitter is equipped with multipleantennas, and the RIS is employed to improve the detection performance. Withoutloss of generality, we adopt the maximum eigenvalue detection approach, andpropose a corresponding analytical framework based on large dimensional randommatrix theory, to evaluate the detection probability in the asymptotic regime.Besides, the phase shift matrix of the RIS is designed with only thestatistical channel state information (CSI), which is shown to be quiteeffective when the RIS-related channels are of Rician fading or line-of-sight(LoS). With the designed phase shift matrix, the asymptotic distributions ofthe equivalent channel gains are derived. Then, we provide the theoreticalpredictions about the number of reflecting elements (REs) required to achieve adetection probability close to 1. Finally, we present the Monte-Carlosimulation results to evaluate the accuracy of the proposed asymptoticanalytical framework for the detection probability and the validity of thetheoretical predictions about the number of REs required to achieve a detectionprobability close to 1. Moreover, the simulation results show that the proposedRIS-enhanced spectrum sensing system can substantially improve the detectionperformance.

RIS-Enhanced Spectrum Sensing: How Many Reflecting Elements Are Required to Achieve a Detection Probability Close to 1?