多IRS辅助的NOMA URLLC系统性能优化

Performance optimization for multi-IRS-assisted NOMA URLLC systems

工业自动化等新型无线通信场景具有严格的低时延性和高可靠性需求,在网络中联合使用智能反射面(IRS)、非正交多址接入(NOMA)以及超可靠低时延通信(URLLC)技术能支持海量终端接入,并提供更低的通信时延、更高的可靠性,以及更高的吞吐量性能。考虑多IRS辅助的NOMA URLLC系统在多个用户被划分为多个簇的情况下,用户簇和IRS如何最佳配对和通信资源如何优化的问题,研究了联合优化用户发射功率分配、IRS反射波束成型以及用户簇IRS配对决策问题,最大化用户的吞吐量之和。为解决所考虑的非凸优化问题,提出一种基于交替迭代算法,通过巧妙地引入松弛变量,并采用半正定松弛方法,高效求解功率分配优化、IRS反射波束成型优化以及用户簇IRS配对决策优化三个子问题。仿真结果表明,所提算法能显著提高系统吞吐量,并且显示了用户簇IRS配对决策优化的必要性与有效性。

New wireless communication scenarios such as automated factories have stringent reliability and low latency requirements.In such wireless networks,the joint application of the intelligent reflecting surface(IRS),non-orthogonal multiple access(NOMA),and ultra-reliable and low-latency communication(URLLC)techniques have the potential to provide lower communication latency,higher reliability,and higher throughput performance,as compared to traditional wireless communication techniques.In a multi-IRS-assisted NOMA URLLC system where multiple users are divided into various clusters,this paper considered the problems of how to pair user clusters and IRSs and how to optimize the communication resource allocation.Specifically,it jointly investigated the user transmit power allocation,IRS reflection beamforming,and user-cluster-IRS pairing decision problems to maximize the sum of user throughputs.To solve the resulting non-convex optimization problem,it proposed an alternating iteration-based algorithm,which solved the three subproblems of power allocation optimization,IRS reflection beamforming optimization,and user cluster IRS pairing decision optimization alternately until achieving convergence by appropriately introducing slack variables and by using the semidefinite relaxation technique.Simulation results show that the proposed algorithm can significantly improve the system’s throughput and verify the necessity and effectiveness of user cluster-IRS pairing decision optimization.