Min–Max Latency Optimization for IRS-Aided Cell-Free Mobile Edge Computing Systems

IEEE Internet of Things Journal, vol. 11, pp. 8757–8770

Abstract

Mobile edge computing (MEC) is expected to provide low-latency computation service for wireless devices (WDs). However, when WDs are located at cell edge or communication links between base stations (BSs) and WDs are blocked, the offloading latency will be large. To address this issue, we propose an intelligent reflecting surface (IRS)-assisted cell-free MEC system consisting of multiple BSs and IRSs for improving the transmission environment. Consequently, we formulate a min–max latency optimization problem by jointly designing multiuser detection (MUD) matrices, IRSs’ reflecting beamforming vectors, WDs’ offloading data size and edge computing resource, subject to constraints on edge computing capability and IRSs phase shifts. To solve it, an alternating optimization algorithm based on the block coordinate descent (BCD) technique is proposed, in which the original nonconvex problem is decoupled into two subproblems for alternately optimizing computing and communication parameters. In particular, we optimize the MUD matrix based on the second-order cone programming (SOCP) technique, and then develop two efficient algorithms to optimize IRSs’ reflecting vectors based on the semi-definite relaxation (SDR) and successive convex approximation (SCA) techniques, respectively. Numerical results show that employing IRSs in cell-free MEC systems outperforms conventional MEC systems, resulting in up to about 60% latency reduction can be attained. Moreover, numerical results confirm that our proposed algorithms enjoy a fast convergence, which is beneficial for practical implementation.

Authors 7

1. Nana Li

   Zhengzhou University

   Affiliation as printed

   School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China

2. Wanming Hao

   Zhengzhou University · Huanghe Science and Technology College

   Affiliation as printed

   School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China

   Department of Engineering, Huanghe Science and Technology University, Zhengzhou, China

   Songshan Laboratory, Zhengzhou, China

3. Fuhui Zhou

   Nanjing University of Aeronautics and Astronautics

   Affiliation as printed

   College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China

4. Zheng Chu

   University of Surrey

   Affiliation as printed

   5GIC & 6GIC, Institute for Communication Systems, University of Surrey, Guildford, U.K

5. Shouyi Yang

   Zhengzhou University

   Affiliation as printed

   School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China

6. Osamu Muta

   Kyushu University

   Affiliation as printed

   Center for Japan–Egypt Cooperation in Science and Technology, Kyushu University, Fukuoka, Japan

7. Haris Gacanin Aachen Institute for Communication Technologies and Embedded Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Communication Technologies and Embedded Systems, RWTH Aachen University, Aachen, Germany