Abstract
In this paper, we aim to provide reliable user connectivity and enhanced security for computation task offloading. Physical layer security is studied in a wireless-powered non-orthogonal multiple access (NOMA) mobile edge computing (MEC) system with a nonlinear energy-harvesting (EH) user and a power beacon (PB) in the presence of an eavesdropper. To further provide a friendly environment resource allocation design, wireless power transfer (WPT) is applied. The secure computation efficiency (SCE) problem is solved by jointly optimizing the transmission power, the time allocations for energy transfer, the computation time, and the central processing unit (CPU) frequency in the NOMA-enabled MEC system. The problem is non-convex and challenging to solve because of the complexity of the objective function in meeting constraints that ensure the required quality of service, such as the minimum value of computed bits, limitations on total energy consumed by users, maximum CPU frequency, and minimum harvested energy and computation offloading times. Therefore, in this paper, a low-complexity particle swarm optimization (PSO)-based algorithm is proposed to solve this optimization problem. For comparison purposes, time division multiple access and fully offloading baseline schemes are investigated. Finally, simulation results demonstrate the superiority of the proposed approach over baseline schemes.
Highlights
The rapid advances in fifth-generation (5G) wireless networks have improved cutting-edge technology requirements, such as support for massive connectivity due to the proliferation of Internet of Things (IoT)devices and growth in the amount of data in modern society [1]
We study a wireless-powered multi-user non-orthogonal multiple access (NOMA)-enabled mobile edge computing (MEC) system assisted by a power beacon (PB) in the presence of an eavesdropper, as illustrated in Figure 1, where the access point (AP) provides the wireless power transfer (WPT) service for M users and a nonlinear EH user
We develop a low-complexity resource allocation scheme based on the particle swarm optimization (PSO) algorithm for secure computation efficiency (SCE) maximization in a wireless-powered NOMA-MEC system with a nonlinear EH user and in the presence of an eavesdropper
Summary
The rapid advances in fifth-generation (5G) wireless networks have improved cutting-edge technology requirements, such as support for massive connectivity due to the proliferation of Internet of Things (IoT). In our previous works [1,18], the PSO technique has been investigated and applied for maximizing the secrecy sum rate and the secrecy energy efficiency of a cooperative NOMA network, respectively In both cases, the results showed that the proposed PSO-based method accomplished yield very close to that obtained by the optimal exhaustive search method, but with the benefit of low computational complexity. We analyze the optimization problems in related references and the reason why those approaches can not be used in this paper This motivated us to introduce PSO as a potential optimization solution in an innovative wireless-powered NOMA-enabled MEC system with a practical non-linear EH user. We provide a low-complexity PSO-based solution for the proposed challenging non-convex optimization problem, which maximizes SCE by satisfying the QoS requirements of NOMA users and meeting the minimum energy harvested by non-linear EH users.
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