Research On Multi-User Mobile Edge Computing Offloading Of NOMA Network

Next-generation wireless networks are expected to support a large number of computationintensive and delay-sensitive applications.Since many devices are computing and power constrained,traditional mobile cloud computing(MCC)is susceptible to the impact of long propagation distances from mobile devices to the cloud,resulting in inability to meet critical latency requirements.Different from MCC,mobile edge computing(MEC)provides cloud computing services for mobile devices by deploying servers at the network edge,so it is considered a promising way to enhance computing services.In addition,to support task offloading between multiple users in a MEC system,blocks of wireless communication resources(such as time,frequency,and so on)need to be utilized efficiently.Designing a suitable multiple access scheme in MEC systems is one of the most important methods.Unlike orthogonal multiple access(OMA)technologies,non-orthogonal multiple access(NOMA)technology allows the allocation of the same resource block to multiple users to improve spectral efficiency and network connectivity.It is a challenging task to optimize the unloading strategy in pursuit of low delay,low energy consumption and high reliability.Therefore,this thesis studies the multi-user mobile edge computing unloading problem based on NOMA,and proposes multi-user computing offload schemes with high efficiency of single assistant collaboration and large total amount of multi assistant collaboration.The main work and innovation points are as follows:(1)The NOMA and user collaboration technology assisted upward moving edge computing to maximize unloading efficiency is investigated,and a joint optimization problem is proposed to maximize unloading efficiency by adjusting unloading time and power allocation.In order to solve this problem,a closed expression of the unloading interrupt probability is derived,and the non-convex problem is transformed into a relaxation problem by using the continuous convex approximation method.The simulation results analyze the interrupt performance of the system,and show that the proposed unloading method can achieve higher unloading efficiency than other schemes.(2)This thesis studies the computing unload of multi-assistant cooperative MEC system based on NOMA.Firstly,this thesis considers the system with users,multiple assistants,and base stations(BS)supported by wireless power transformer(WPT),through the use of NOMA and user collaboration technology to improve the total amount of data offloading system,when there is no strong direct transmission link between the user and BS,the user can use NOMA to offload their computatively intensive tasks to the assistant at the same time.The assistant can calculate and unload these tasks through NOMA.Then,in order to solve the nonlinear constrained multivariable optimization problem,the interior point method is adopted.In this method,the penalty function is added to the objective function to make the inequality constraints not work,and the optimal unconstrained solution is ensured within the feasible region.Finally,the simulation results show that compared with other benchmark schemes,the proposed multi-assistant collaborative MEC system scheme based on NOMA significantly increases the total unload data volume under delay constraints.