Multi User Optimizationof NOMA Based On Mobile Edge Computing

With the rapid development of mobile communication technology and the global digital economy,the demand for communication technology in society is increasing.The arrival of the 5th Generation Mobile Communication Technology(5G)has brought us many new application scenarios,such as the Internet of Vehicles,intelligent manufacturing,wireless healthcare,smart homes,drones,etc.These scenarios have higher requirements for latency,energy consumption,throughput,etc,The traditional Orthogonal Multiple Access(OMA)technology is no longer able to meet these needs.Non-Orthogonal Multiple Access(NOMA)technology allows multiple users to access the same frequency band simultaneously,greatly increasing the accessibility of devices and improving data processing capabilities.At present,such applications require a large amount of computation on the mobile terminal,but the computing power of mobile devices cannot fully meet this requirement.Mobile edge computing(MEC)can effectively solve this problem.Combining NOMA and edge computing technologies,this paper mainly does the following two works:(1)In order to improve the throughput of users unloading in mobile edge computing,a MEC unloading strategy of hybrid OMA-NOMA is proposed by combining the traditional OMA technology with NOMA technology.Then,a multi-objective optimization model is constructed,and a low complexity successive optimization algorithm is proposed to maximize the system capacity.The closed form solution of the optimal power allocation is derived and it is proved to comply with the Pareto optimal solution criterion.Finally,its performance is simulated,Simulation has proven the effectiveness of this scheme.The experimental results indicate that using a hybrid OMA-NOMA strategy can effectively improve system capacity.(2)In order to reduce the energy consumption of multi-user unloading in mobile edge computing,users and channels are matched bilaterally through user matching algorithm.Then,a hybrid OMA-NOMA MEC offloading strategy is applied to propose a joint optimization scheme for user pairing and power allocation.A multi-objective optimization model is constructed with the goal of minimizing system energy consumption.Then,a low complexity successive optimization scheme is used to derive a power allocation closed form solution that conforms to the Pareto optimality criterion.Finally,the effectiveness of the algorithm proposed in this paper is demonstrated through experiments.The experimental results show that the proposed joint optimization scheme can effectively reduce the energy consumption of users during unloading.