Radio Resource Allocation Algorithms For M2M Communication System

Machine-to-Machine(M2M)communications are expected to play a major role in future 5G networks.In M2 M communication networks,machine type communications devices(MTCDs)are allowed to communicate with each other or with the infrastructures under reduced human intervention to achieve intelligent identification,positioning,tracking,monitoring and management,etc.However,the massive MTCDs attempt to access the network simultaneously,the M2 M communication networks overload issue will arise accordingly and the diversity of MTCD service requirements pose challenges to the radio resource management of networks.In this thesis,the radio resource allocation algorithms of M2 M communication networks are studied,and the main contents are as follows:Firstly,the research background,the architecture and characteristics of M2 M communication networks are introduced.On this basis,this thesis focus on the wireless resource management technologies.The cell selection algorithms,power allocation algorithms and joint random access and resource allocation algorithms for M2 M communication networks are summarized and analyzed,emphasizing the importance of joint resource allocation algorithms.We study the network lifetime maximization problem of an M2 M communication network consisting one base station(BS)and a number of MTCDs,and propose to achieve the objective through designing joint mode selection and resource allocation scheme.We transform the network lifetime maximization problem as a residual energy maximization problem,and formulate the joint mode selection and resource allocation problem as an optimization problem which maximizes the residue energy of all the MTCDs.As the formulated optimization problem is nonconvex,which cannot be solve easily using traditional optimization tools,we transform it into convex one through mathematical manipulations and then solve the problem to obtain the optimal resource allocation strategy of the MTCDs by applying Lagrange dual method.We also jointly study the issues of random access,cell selection and resource allocation of an M2 M communication networks which including a number of MTCDs and BSs,and propose a joint access class barring(ACB),cell selection and resource allocation algorithm which consists of two sub-algorithms: virtual clustering-based joint ACB and resource block(RB)allocation sub-algorithm and utility function maximization-based joint cell selection and power allocation sub-algorithm.To achieve the efficient usage of the RBs and meet the diverse delay requirements of the MTCDs,we first propose a virtual clustering-based joint ACB and RB allocation sub-algorithm.According to the QoS requirements of the MTCDs,we partition the MTCDs into different virtual clusters with each cluster representing MTCDs with same type of services.We then formulate the problem of ACB and RB allocation of clusters as an optimization problem which maximizes the RB utilization of all the MTCDs,and solve the optimization problem to obtain the optimal ACB factor and RB allocation strategy.Based on the ACB and RB allocation strategy obtained previously,we then design the optimal cell selection and power allocation scheme for individual MTCDs.Introducing the concept of utility function,we define the utility function of the M2 M communication networks and formulate the joint cell selection and power allocation problem as a utility function maximization problem.Since the formulated optimization problem is a mixed-integer nonlinear optimization problem which cannot be solved conveniently.We transformed it into a convex optimization problem and solve the problem by applying iterative algorithm and Lagrange dual method.Thus,the optimal cell selection and power allocation strategy corresponding to the maximum utility function can be obtained.