Wireless Access And Resource Allocation Of 5G New Network Architecture

The last decade has witnessed a tremendous growth in the demand for mobile data traffic,which has led to a dramatic increase in energy consumption in mobile communications networks.The huge energy costs paid by mobile operators are considered one of the most important challenges the next generation of mobile communications networks facing.Although most researches focus on the power optimization of a single physical layer,how to meet the green objective of fifth-generation cellular networks while respecting the users' quality of service becomes an urgent problem to be solved.At present,the basic framework of the wireless access network of the fifth generation mobile communication system has been determined,and the heterogeneous cloud access network is one of the candidate frameworks for its implementation.Recently,a large amount of research work is devoted to improving the energy efficiency of the mobile communication system,which mainly includes the efficient network resource management method and the network energy saving technology.This paper mainly studies: 1)introduce the user traffic rate under the framework of heterogeneous cloud access network and design the high performance energy efficient resource allocation algorithm;2)introduce user tasks offloading under heterogeneous cloud access network and design energy saving algorithm;3)introduce the user experience utility under heterogeneous cloud access network and design multi-objective optimization algorithm.The first chapter firstly elaborates the standard process of the wireless access network architecture of the fifth generation of mobile communication system and the main research focus in the heterogeneous cloud access framework.Then we briefly describe the content and the research results of this paper.Finally,the organization structure of this paper is briefly described.The second chapter mainly studies the efficient resource allocation problem which introduces the user traffic rate in the heterogeneous cloud access network.Firstly,the power consumption model of the entire network is modeled,and the optimization problem of the average energy efficiency of the whole system under the scenario of considering the user traffic arrival rate.Secondly,the original optimization problem is transformed by using fractional programming,norm approximation and Lyapunov optimization.Finally,based on Lagrangian dual decomposition,we propose a two-layer iterative algorithm called EE-DRAA.Besides,the average energy efficiency and actual data length of the system about the control factor are derived.Based on the Earth2.3 model,we carry out system level simulation.The results show the correctness of theoretical deduction and the influence of control factor V on resource allocation.Compared to the existing research on heterogeneous access networks efficiency,the main contribution of this chapter is to consider the impact of user traffic arrival rate on user access and resource optimization problem.The optimization goal of this chapter is the average energy efficiency of the system.The third chapter mainly studies the energy saving problem of heterogeneous cloud access network which introduces user task offloading characteristic.Firstly,the network model,transmission model and computational model are modeled.Secondly,the optimization problem of minimizing user side energy consumption under a series of constraints such as user task constraint and system resource constraint is modeled.Then,based on the information of the user tasks' characteristics and channel status,we propose a sort based heuristic energy saving algorithm.Finally,the system level simulation results verify the effectiveness of the proposed algorithm.Unlike most researches considering the users offloading of heterogeneous access network,the main contribution of this chapter is that we consider the scenario where there are multiple servers and the optimization goal is to minimize the energy consumption of the system user side.What's more,we jointly optimize the user server association matrix.,uplink beamforming matrix and the users' transmission power vector.The fourth chapter focuses on the problem of joint optimizing user experience utility and task delay.Considering about the mobile users' tasks offloading to the cloud server,firstly we discuss the network model and time delay model of the system.Secondly,the user experience utility function of user data is defined.Thirdly,the joint optimization problem of user experience utility and task delay is modeled.Then,based on the properties of optimization variables,the original optimization problem is transformed into two iterative sub-optimization problems by using block coordinate descent method.Finally,the system level simulation results verify the effectiveness of the proposed algorithm.Different from previous research on heterogeneous access network's energy consumption or energy efficiency problem,the main contribution of this chapter is that we jointly optimize the user experience and task delay time.We study how user experience utility influence the network resource allocation.The fifth chapter further summarizes the content and work of this paper and makes suggestions of future research directions of the heterogeneous cloud access network.