Performance Analysis Of Energy Efficiency/spectral Efficiency And High Energy Efficiency Design In Heterogeneous Network

With the continuous development of the information and communication technology(ICT) industry, the traffic in mobile communication network increases exponentially due to the diversity of user terminals and applications. Existing network can no longer effectively support the mobile data deluge, this new problem requires an evolutionary network architecture to provide service for the high traffic with dynamic nature in time and space domain. Recently, heterogeneous network turns out to be a new choice for the major operators as the new network architecture. This architecture consists of multiple types of base stations, with different transmit power, carrier frequency, and deployment density, etc. It can provide personalized and low cost service for users, which have different moving speed, traffic demand and multiple types of traffic, through coverage area overlapping.However, network energy consumption, as the growing serious problem, has become the focus of operators. The statistic data of the world’s leading operators, such as Vodafone and China Mobile, shows that, as the exponential growth of traffic volume and the increasing deployment density of base stations, the network energy consumption of base station is rapidly rising. So, the operators need to pay high fee to the energy cost. On the other hand, carbon emissions associated with the huge energy consumption is also an environmental issue which can’t be ignored. Therefore, there exist requirement to research the realization of energy efficient network deployment, base station operation mode management and resource allocation method, based on the traffic distribution, user mobility mode, traffic requirement and user behavior. Also, it is the new problem, which academia and industry both concerned recent years.In recent 5 years, there are several research work about base station sleeping and energy efficient resource allocation in academia. In this paper, aiming at this problem, further research work has been carried out: firstly, propose a correlation forecasting index based on the dynamic characteristics of traffic in time and space domain, propose a decision strategy of base station operation mode based on the index; secondly, propose a decision method of the optimal association matrix between user equipments and base stations in heterogeneous network based on the energy consumption of different type of base stations; thirdly, propose an energy efficient resource allocation framework for multiple traffic coexisting network, then evaluate the effectiveness of proposed method with the simulation results.The first chapter provides an overview of main problem and research focus, explains the research work and contributions, describes the framework of this thesis.On the network perspective, the second chapter researches the distribution correlation of traffic in space and time domain, and proposes a prediction index about the distribution correlation of traffic, then, based on this index, proposes a new scheme about the energy efficient operation modes of base stations in heterogeneous network. The main innovation of this work is to research the effect of prediction window length on the energy saving and system performance, finally, the simulation results further demonstrate the effectiveness of this scheme.On the user equipment perspective, the third chapter researches the optimal association matrix between user equipments and base stations in heterogeneous network. The core of this problem is how to choose the base station, which cause lowest energy consumption and meet the quality of service(QoS), from the base station set. In this thesis, we first formulate the total energy consumption of system according to different types of base station’s energy consumption, then, based on Majorization-Minimization method, the original problem is converted into a linear combination optimization problem, finally, propose a suboptimal association algorithm.For orthogonal frequency division multiple access(OFDMA) heterogeneous networks, the fourth chapter researches the energy efficient resource allocation when multiple traffics coexist. Generally, the multiple traffics are classified into two classes: delay sensitive traffic and delay non-sensitive traffics. Firstly, we formulate the model of system energy efficiency with multiple traffics coexist, and then further decompose the complex optimization problem, propose an optimal subchannel and transmit power allocation policy through the Lagrange dual approach, finally, evaluate the algorithm in heterogeneous network. The simulation results show the energy efficiency gain of the proposed method when multiple traffics coexist.The fifth chapter summarizes the content of this thesis, and point out the research directions in the future and some corresponding research suggests.