Joint Task Offloading and Resource Management in NOMA-Based MEC Systems: A Swarm Intelligence Approach

In this paper, we study the issue of computation offloading in non-orthogonal multiple access (NOMA)-based multi-access edge computing (MEC) systems. A joint optimization problem of offloading decision, subchannel assignment, transmit power, and computing resource allocation is investigated to improve system performance in terms of both completion time and energy consumption. The formulated problem is a mixed-integer non-linear programming one, it is therefore hard to solve. To make the problem tractable, we first decompose the problem into subproblems of computing resource allocation (CRA), transmit power control (TPC), and subchannel assignment (SA). Then, we address the CRA subproblem by a convex optimization technique. For the remaining two subproblems TPC and SA, we propose to use a gradient-free swarm intelligence approach, namely whale optimization algorithm, to provide a very general but efficient solution. Computer simulations are performed to show the convergence of the proposed algorithm, also its better performance in comparison with conventional schemes.