Computation rate maximization in multi-user cooperation-assisted wireless-powered mobile edge computing with OFDMA

In the era of Internet of Things (IoT), mobile edge computing (MEC) and wireless power transfer (WPT) provide a prominent solution for computation-intensive applications to enhance computation capability and achieve sustainable energy supply. A wireless-powered mobile edge computing (WPMEC) system consisting of a hybrid access point (HAP) combined with MEC servers and many users is considered in this paper. In particular, a novel multiuser cooperation scheme based on orthogonal frequency division multiple access (OFDMA) is provided to improve the computation performance, where users can split the computation tasks into various parts for local computing, offloading to corresponding helper, and HAP for remote execution respectively with the aid of helper. Specifically, we aim at maximizing the weighted sum computation rate (WSCR) by optimizing time assignment, computation-task allocation, and transmission power at the same time while keeping energy neutrality in mind. We transform the original non-convex optimization problem to a convex optimization problem and then obtain a semi-closed form expression of the optimal solution by considering the convex optimization techniques. Simulation results demonstrate that the proposed multi-user cooperation-assisted WPMEC scheme greatly improves the WSCR of all users than the existing schemes. In addition, OFDMA protocol increases the fairness and decreases delay among the users when compared to TDMA protocol.