Research On Resource Optimization Of NOMA-Based Mobile Edge Computing Systems

Driven by the growing of computing-intensive applications in future networks,Mobile Edge Computing(MEC)is considered to be an effective technology to relieve the pressure on mobile terminals.MEC technology allows users to offload their computing workloads to a MEC server with rich computing and caching capabilities located near the base station(BS).Facing with a large number of offloading requirements,how to use limited communication resources and computing resources to provide services to users has become a key issue in MEC systems.Besides,Non-Orthogonal Multiple Access(NOMA)can realize spectrum multiplexing through Superposition Coding(SC)technology and Successive Interference Cancellation(SIC)technology,thereby improves spectrum efficiency.This thesis studies the resource optimization problems in NOMA-based MEC systems.By using advanced NOMA technology,the offloading efficiency of the MEC systems can be improved.The main work and contributions are as follows:(1)For the single MEC server scenario,a joint offloading decision-making and power and time resource allocation scheme for a NOMA-based MEC system with user cooperation is proposed.The system contains two ordinary users,an auxiliary user and a MEC server located near the BS.It is assumed that both ordinary users and auxiliary users have computing needs.It is also assumed that there is no direct communication link between ordinary users and the BS.Two ordinary users can use NOMA technology to offload part of the computing tasks to the auxiliary user,and then the auxiliary user can offload part of the computing tasks to the MEC server.Under the user delay requirements,the task offloading decision,transmission power and time allocation are jointly optimized,and the goal is to minimize the weighted sum of user energy consumption.The simulation results show that the proposed scheme can effectively reduce user energy consumption compared with the traditional OMA and non-cooperative schemes.(2)For the multi-MEC server scenario,a multi-dimensional resource allocation scheme is proposed,which jointly optimizes the channel allocation,server allocation,uplink and downlink transmission power,and the allocation of computing resources.The goal is to minimize the total offloading delay of all users.This problem is a Mixed Integer Nonlinear Programming(MINLP)problem.In order to solve this problem,this thesis proposes an effective iterative algorithm.Specifically,the problem is first transformed into a two-layer matching problem,and then for a given two-layer matching,the problem is solved in two steps.The two-layer matching is obtained through multiple iterations of the exchange matching algorithm.The simulation results show that,compared with the OMA-based offloading scheme and the scheme that does not consider the channel allocation optimization,the proposed resource allocation algorithm can effectively reduce the system offloading delay.