Research On Methods Based On NOMA And Mobile Edge Computing

With the rapid development of the Internet of Things and 5G,a large number of smart devices and emerging applications have emerged.NOMA technology achieves higher spectral efficiency by allowing multiple users to share the same time or space or code resources and employing successive interference cancellation at the receiver,thus enabling large-scale connection and deployment of many smart devices.Mobile edge computing technology achieves the purpose of reducing system latency and improving service quality by offloading computing resources required by users to base stations with computing capability in nearby or wireless access networks,thus fulfilling the latency-sensitive needs of emerging applications.Combining NOMA with mobile edge computing technology can solve many problems faced by smart devices and emerging applications in the current development of the Internet of Things and 5G.This paper studies the scheme design based on NOMA and mobile edge computing technology.The details are as follows:Firstly,for the network based on NOMA and mobile edge computing with malicious eavesdroppers,a scheme to maximize anti-eavesdropping capabilities under the premise of ensuring secure offloading is proposed.For the two NOMA users considering the uplink offloading model,the goal is to maximize the minimum anti-eavesdropping ability of the two users under the constraints of the worst-case security rate and transmission rate.The feasibility of the problem is analyzed first,then an iterative algorithm is proposed to obtain a closed-form solution to the optimization variables.Finally,the simulation results verify the correctness of the theoretical analysis and the superiority of the proposed algorithm over other benchmark schemes.Secondly,for a network based on NOMA and mobile edge computing with malicious eavesdroppers,a scheme to minimize the task completion delay of the user while ensuring secure offloading is proposed.Consider the worst-case security rate,outage probability,and transmission rate constraints to minimize the maximum task completion delay among all users.Since the proposed problem is a non-convex problem,after deriving some important insights,an algorithm based on binary search is proposed to obtain the optimal solution of the original problem.The final numerical simulation results also show that the proposed algorithm has certain advantages.Finally,a resource allocation scheme with minimal energy consumption is proposed for the UAV-assisted NOMA mobile edge computing network.The UAV is highly mobile and flexible,and can serve as a mobile edge computing server for ground users.Among the multiple users on the ground,two users are paired into a group,the users in a group use NOMA to transmit,and the group to group uses TDMA to transmit.Considering the energy minimization problem of the whole system,due to the non-convexity of the problem,an alternating optimization algorithm is proposed,and the solution of the original problem is obtained by using the successive convex approximation method.The simulation analysis verifies the convergence of the algorithm and the superiority over other benchmark schemes.