Transmission Design in Secure URLLC Network Assisted by Reconfigurable Intelligent Surfaces

Abstract

In this work, we focus on the secure transmission in reconfigurable intelligent surface- (RIS-) aided ultrareliable low-latency communications (URLLC) network. Specifically, we investigate the average effective secrecy rate (AESR) optimization via jointly designing the transmit beamforming, the artificial noise covariance at the transmitter (Tx), and the phase shifter at the RIS. Particulary, the AESR in URLLC network contains not only the commonly used information rate expression based on long codewords but also two penalty terms about the decoding error probability introduced by finite block-length coding. Thus, the AESR is a nonconcave objective. In addition, the unit modulus constraint of the reflecting coefficient at the RIS is nonconvex, which makes the formulated problem difficult to handle. To solve the formulated highly nonconvex problem, we first decouple the complicated objective into a linear function by introducing several slack variables. Then, we address the nonconvex constraints by the first-order expression and the penalty concave-convex procedure (PCCP) technique. Thus, an alternating optimization (AO) technique is proposed to solve the reformulated problem, where the convergence can be guaranteed by rigorous proof, and the computational complexity is a polynomial function of the main system parameters. Simulation results demonstrated the performance of the proposed design as well as the superiority of RIS in improving the secrecy performance when comparing with other baselines.