Latency minimization for IRS-assisted mobile edge computing networks

In this paper, we consider the latency minimization problem via designing intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) networks. For the scene when local users cannot complete all computing tasks independently, a common solution is transferring tasks to cloud servers. We consider that the MEC system contains multiple independent users, and each user sends task data to the base station in a partially offloaded manner. Our goal is to minimize the maximum latency for all users. The original problem is strongly non-convex, which caused difficulty to solve. We first introduce a new variable to transform the max–min problem into an alternative minimization problem, and then solve each optimization variable separately by the block coordinate descent method. Finally, our simulation experiments demonstrate that our proposed scheme obtain better performance with respect to other existing schemes.