부산대학교 도서관

To reduce the computing delay of the terminals and improve the poor wireless channel environment, in this paper, a computing resource allocation algorithm for IRS-assisted edge computing is proposed. By introducing the intelligent reflecting surface (IRS) technique to reduce the edge computing latency, the computing offloading variables are optimized through an Alternating optimization approach, and a partial offloading strategy for MEC offloading is adopted. Deep reinforcement learning (DRL) is applied for coarse phase control of the IRS, and fine phase control of the IRS is achieved through fine phase optimization. In simulations, the proposed scheme is demonstrated to be effective and low latency.