Research On Radio Resource Allocation Algorithms For 5G Multi-service Scenarios

In past few decades,mobile communication technologies experienced rapid developments and have changed society and human lives deeply.Recently,domestic and foreign operators are actively deploying the 5th generation mobile communication systems(5G)to meet the more stringent and extensive communication demands of the information.However,in the coexistence scenario of 5G multi-services,various user quality of service requirements,the diverse granularity of time-frequency resource allocation of different services and the resource competition of multiple users pose new challenges to the radio resource management of 5G.How to design efficient resource allocation algorithms under the consideration of various service requirements,available system resources and complex network states is an important problem to be tackled.This thesis mainly studies 5G multi-service scenarios-oriented radio resource allocation and user association problems.The specific research contents are as follows:On the basis of an overview of 5G application scenarios,system architecture and key technologies,this thesis elaborates 5G radio resource management technology,analyzes and summarizes the research status of radio resource allocation and user association algorithms for 5G systems.The joint power allocation,sub-channel selection and non-orthogonal multiple access(NOMA)pairing problem is studied for a 5G data transmission scenario offering multiple types of user services.Considering the constraints of different service rate requirements,power limits and available system resources,the joint resource allocation problem is formulated as the problem of maximizing the total energy efficiency of the system.The formulated optimization problem is a non-deterministic polynomial-hard(NP-hard)problem,and is difficult to solve directly.Thus,the original problem is transformed into two sub-problems,i.e.,power allocation sub-problem,channel selection and NOMA matching sub-problem.For the power allocation sub-problem,the Lagrange universal solution of user transmit power which achieves optimal energy efficiency is derived.For channel selection and NOMA matching sub-problems,a Kuhn-Munkres(K-M)algorithm-based heuristic method is proposed to optimally design user access mode selection,NOMA pairing and channel allocation strategy.In an 5G end-to-end transmission scenario supporting multiple services,this thesis studies the problem of joint user association,route selection and resource allocation.Considering the constraints of different user rates and bandwidth requirements,power limits and available resources,the joint user association,routing and resource allocation problem is formulated as an system energy consumption minimization problem.For single user transmission scenario,the optimization problem is NP-hard,which is difficult to solve.Thus,we firstly transform the original problem into two sub-problems,i.e.,power allocation sub-problem,user association and routing sub-problem.Then,the two sub-problems are solved based on the Lagrange dual algorithm and the Dijkstra-shortest path algorithm respectively to determine the power allocation,user association and routing strategy of a single user.The optimal strategy of single-user scenario is extended to multi-user scenario,and a heuristic algorithm is proposed based on the minimum offset cost and bankruptcy game so as to solve the problem of multi-user bandwidth allocation and link capacity competition,and then the minimum system energy consumption can be obtained.