Latency Minimization for Full-Duplex Mobile-Edge Computing System

Abstract

Mobile-edge computing (MEC) which employs cloud computing platforms at the network edge is an emerging paradigm for 5G networks. Users can be provided with lower latency and energy consumption by offloading computation tasks to the edge cloud. However, it is hard for MEC to guarantee low latency when large amount of users share the limited spectrum resource to offload computation tasks or download computation results because of high transmission delay. Full-duplex (FD) communication that allows simultaneous transmission and reception of signals over the same frequency band, is a promising solution to the shortage of spectrum resource. In this paper, we investigate a novel multi-user FD-MEC system involving both offloading and downloading processes. With the help of the FD capable BS, two half-duplex (HD) users can form a FD pair which can share the same time slots and frequency band for uplink and downlink transmission. To minimize the completion time of all users in the system, we formulate a joint optimization problem of time, power and user pairing scheme, which is a mixed-integer nonlinear programing (MINLP). This problem is further divided into two layers. For the inner layer problem, we obtain the optimal solution by a bisection method. While for the outer layer problem, we use concave-convex procedure (CCCP) to transform it into a tractable form and obtain a stationary point. Finally, numerical results show that with our proposed resource allocation scheme, the overall latency can be significantly reduced by introducing FD to MEC system.