Abstract
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.
Highlights
To cope with various performance requirements of emerging applications in fifth-generation (5G) and beyond networks, different advanced solutions have been taken into account, simultaneously
As will be presented the solution for the computing resource allocation (CRA) is solved by a convex optimization technique, as presented in the previous works, while the solutions for the transmit power control (TPC) and subchannel assignment (SA) subproblems are obtained by WOA
In this paper, we studied the issue of computation offloading in non-orthogonal multiple access (NOMA)-based multi-access edge computing (MEC) systems
Summary
To cope with various performance requirements of emerging applications in fifth-generation (5G) and beyond networks, different advanced solutions have been taken into account, simultaneously. Among them, developed by the European Telecommunications Standards Institute (ETSI), multi-access edge computing (MEC) is a highly useful technology [1]. The principle of MEC is to move the computation capacity from the cloud to the network edge in the proximity of user equipments (UEs). Thanks to this mechanism, UEs can offload their computation tasks to MEC servers while significantly reducing the whole network transmission latency. Non-orthogonal multiple access (NOMA) has been well known as an essential technique beyond 5G to cope with the massive Internet of Things (IoT) connectivity [2], [3]. The primary idea of NOMA is to carry over the
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