Joint Offloading Decision and Resource Allocation in MEC-enabled Vehicular Networks
Lintao Zhang, Yanglong Sun, Yuliang Tang, Hao Zeng, Yuqi Ruan
Abstract
The high mobility of vehicles in mobile edge computing (MEC) enabled vehicular networks causes the channel estimation error which will influence the quality of service (QoS) of users. In this paper, we explore the computation offloading and resource allocation in orthogonal frequency-division multiple access (OFDMA) based vehicular networks considering the imperfect channel state information (CSI). A mixed integer non-linear programming (MINLP) is formulated to minimize the offloading latency. To tackle this NP-hard problem, we divide the offloading and resource allocation into two subproblems which are offloading decision subproblem and resource allocation sub-problem. Specifically, given the offloading decision, we design a coalition game based algorithm to solve the subcarrier assignment problem and a convex optimization method to solve the power allocation problem. Meanwhile, given the resource allocation, we finally get the offloading decision by solving the linear programme (LP) problem. Numerical results show that the proposed scheme can significantly reduce the offloading latency.