Reliability optimization in IRS-assisted UAV networks

Abstract

Unmanned aerial vehicles (UAVs) and intelligent reflecting surfaces (IRSs) are regarded as critical technologies which need to be developed for the sixth-generation mobile network (6G). In this paper, we study the reliability of the IRS-assisted Unmanned aerial vehicles (UAV) communication system with limited UAV energy in complex urban scenarios. We present the problem by joint optimization of the IRS's scheduling, the UAV's trajectory, the IRS's phase shift, and the UAV's transmit power for maximizing the reliability of the transmission link under the constraints of UAV energy and channel error rate. The concavity of the problem is difficult to judge, and the problem is hard to find a substitution function to convert it into a tractable form. Therefore, we design a chaotic adaptative hybrid whale optimization algorithm (CAHWOA) to address the problem. CAHWOA is implemented by using alternately the chaotic adaptation whale optimization algorithm (CAWOA) and the variational perturbation binary whale optimization algorithm (VPBWOA). CAWOA and VPBWOA are used for solving the continuous variable subproblem and the binary variable subproblem, respectively. The numerical results show that the joint optimization of IRS and UAV improves the transmission link reliability by nearly 30% compared with the two baseline schemes. CAHWOA can improve the convergence rate by about 18% compared with the baseline algorithms. Meanwhile, it can enhance the optimization-seeking accuracy by about 0.04.