Min-Max Latency Optimization for Intelligent Reflecting Surface-Assisted Mobile Edge Computing

Computation offloading has been regarded as an effective scheme to reduce the latency in mobile edge computing (MEC) system. However, the offloading latency will be extremely increased when the propagation link is poor. To improve the offloading performance, we apply the intelligent reflecting surface (IRS) to the MEC system, and propose an IRS-assisted MEC system. We formulate a min-max user latency problem by jointly optimization of offloading strategy, computing resources and IRS phase shift. To solve the non-convex problem, we propose an alternate iterative algorithm to decouple it into two subproblems. In particular, the successive convex approximation and semidefinite relaxation techniques are exploited to solve the two subproblems, respectively. The simulation results show that, compared with the traditional scheme, the proposed scheme can effectively improve user's fairness and reduce the user's latency.