Research On Resource Allocation For NOMA-based Edge Computing

With the continuous deployment and application of the Internet of Things(Io T),a large number of intelligent devices are connected to the network,which has created a huge demand for network communication and computing resources,and edge computing can provide abundant resources for different applications running on these devices nearby to meet these needs.By deploying edge computing servers(ECS)at the edge of the network,these devices can offload computing tasks to ECS for processing,thereby reducing processing latency and energy consumption.In the task offloading of edge computing,Io T devices need to offload tasks to ECS through wireless channels.Traditional Orthogonal Multiple Access(OMA)has insufficient bandwidth resources when facing massive device access.This is because OMA needs to allocate orthogonal time domain or frequency domain resource blocks to each user,but the resource blocks that can be allocated are limited.Non-Orthogonal Multiple Access(NOMA)enables multiple users to share the same time-frequency resource block,so as improving the spectral efficiency and capacity of the wireless network,effectively alleviating the access of a large number of devices and the limited bandwidth resources contradiction between.Generally,compared with OMA,NOMA has better communication performance,but NOMA also means that multiple users share the same time-frequency resources.If all users use NOMA for transmission,it may cause some tasks with high latency requirements cannot be completed on time.By adopting OMA,the user can transmit separately and reduce the latency of the user.Therefore,the hybrid transmission scheme of NOMA and OMA may have better system performance.However,in the edge computing based on NOMA and OMA transmission,the allocation of many resources is involved,and the resulting joint optimization of communication,computing,power and other resources is still quite challenging.Therefore,this thesis focuses on task offloading in edge computing,and in the multi-user scenario based on NOMA transmission,research on resource allocation is carried out to reduce system energy consumption.The main work and innovations of this thesis are as follows:(1)Applying NOMA and OMA transmission to edge computing,and combining task offloading decision,computing and power resource allocation,the problem of minimizing system energy consumption is studied under the condition of satisfying user latency requirements.For the non-convex optimization problem,firstly,through the method of variable substitution,the non-convex function of the target is equivalently converted into a convex function,and by relaxing the upper and lower bounds of the non-convex function in the constraint,the upper and lower bound convex optimization problem of the original problem is formed respectively.Then for the upper and lower bound convex problem,an iterative algorithm based on branch and bound is designed,so that the upper and lower bounds can be gradually approached in the process of continuous branching,and the optimal solution of the original problem can be obtained.Finally,the effectiveness of the algorithm is verified by simulation and the transmission schemes of NOMA and OMA are superior to other schemes in system energy consumption.(2)In the edge computing system based on NOMA,the access control of users under multiple base stations is considered,and the minimization of system energy consumption is studied by combining task offloading decision,computing and communication resource allocation and power control.In order to solve the non-convex mixed integer problem,it is divided into three sub-problems and solved separately.Among them,the task offloading sub-problem and the computing and communication resource allocation sub-problem can obtain optimal solutions through their convexity,and the base station selection and power control sub-problems are designed with a heuristic algorithm through convex approximation.Finally,combining the three sub-problems,a low-complexity iterative solution algorithm is designed,and the effectiveness of the NOMA-based user access scheme is verified by simulation.