  In this paper, we propose an reconfigurable intelligent surface (RIS)
enhanced spectrum sensing system, in which the primary transmitter is equipped
with single antenna, the secondary transmitter is equipped with multiple
antennas, and the RIS is employed to improve the detection performance. Without
loss of generality, we adopt the maximum eigenvalue detection approach, and
propose a corresponding analytical framework based on large dimensional random
matrix theory, to evaluate the detection probability in the asymptotic regime.
Besides, the phase shift matrix of the RIS is designed with only the
statistical channel state information (CSI), which is shown to be quite
effective when the RIS-related channels are of Rician fading or line-of-sight
(LoS). With the designed phase shift matrix, the asymptotic distributions of
the equivalent channel gains are derived. Then, we provide the theoretical
predictions about the number of reflecting elements (REs) required to achieve a
detection probability close to 1. Finally, we present the Monte-Carlo
simulation results to evaluate the accuracy of the proposed asymptotic
analytical framework for the detection probability and the validity of the
theoretical predictions about the number of REs required to achieve a detection
probability close to 1. Moreover, the simulation results show that the proposed
RIS-enhanced spectrum sensing system can substantially improve the detection
performance.
