关键词: 车—车网络, 智能反射面, 认知非正交多址接入, 物理层安全

Abstract: Cognitive non-orthogonal multiple access (NOMA) and intelligent reflecting surface (IRS) have been envisioned as two promising technologies for vehicle to everything due to their high spectral efficiency and low power consumption. In this paper, we consider an IRS-aided vehicle to vehicle (V2V) network with cognitive NOMA in the presence of a malicious eavesdropper. Under the realistic assumption of channel estimation errors, we study the physical layer security of IRS-aided V2Vnetwork with cognitive NOMA system from two aspects of security and reliability. The analytical expressions of outage probability and intercept probability under double Rayleigh fading channels are derived. Finally, Monte Carlo simulation is used to validate the theoretical analysis. The results show that the physical layer security performance of V2V network can be further improved by optimizing the source vehicle transmitting power, distance between vehicles, IRS reflection unit number, target rate and power distribution coefficient.

Key words: Vehicle to vehicle, Intelligent reflecting surface, Cognitive non-orthogonal multiple access, Physical layer security