Performance Analysis Of Energy Efficiency/Spectral Efficiency And High Energy Efficient Design In Distributed Antenna System

Distributed antenna system(DAS) has been applied to the heterogeneous network in the fourth generation mobile communication systems long-term Evolution. It is used to improve data link reliability and spectrum efficiency.The need to consider the future dense coverage scenario, how to implement largescale antenna system architecture based on distributed antennas is the concerning focus of academia and industry.However, with the increase of antenna numbers, and to provide high speed mobile data service and improve the user experience rate at the celledge, how to solve the contradiction between the power consumption of wireless access network and the spectrum efficiency becomethe focus of network deployment and resource optimization.Only from the perspective of the spectrum efficiency,the high transmission powerandthe large bandwidth meanshigh system capacity. However, from the perspective of the energy efficiency, we cannot always increase the energy efficiency of the system through improving transmission power and bandwidth, due to the presence of a signal processing energy consumption and the static power. Therefore, we look forward to find out a new resources management method to improve the energy efficiency of wireless communication system.In this paper, the main research work includes: 1)we compare the energy efficiency performance based on the user’s location between the distributed antenna systems and centralized antenna system. 2)we studythe energy-efficient resources allocation of the distributed antenna orthogonal frequency division multiplex(OFDM) system, and puts forward splitting the combinatorial optimization problem into two subproblems. 3)we let the distributed large-scale antenna system(LSAS) as the research object, study the high energy efficiency design and resource allocation problems after splitting the users into clusters.The overview for each chapter is summarized as follows:Chapter 1 summarizes the origin and development of distributed antenna system, and the current status of energy efficiency of the DAS combining with OFDM and LSAS technology, the main content and structure arrangement are given in the next context.Chapter 2 compares energy efficiency performance of distributed antenna system based on user’s location in the single cell with centralized antenna system and deduced the upper and lower bounds of the energy efficiencybased on user’s location, especially compared the performance of energy efficiency when the user is at the cell edge. Then in view of the multi-user scenarios, this paper analyzes the relationship between the energy efficiency and spectral efficiency.Chapter 3 studies the energy-efficient resources allocation of the distributed OFDM system, and puts forward splitting the combinatorial optimization problem into two subproblems, namely carrier allocation and power allocation, and take the user rate proportional fairness into consideration.Then we can make each antenna optimal in energy efficiency in order to achieve sub-optimal of the whole system in energy efficiency, and we can obtain the power value of each sub-carrier by finite iteration with the sub-gradient algorithm.Chapter 4 studies the high energy-efficient design of the distributed large-scale antenna system. The object of study is the effective energy efficiency of system with adaptive modulation. We propose assign each user to the suitable distributed antennas based on the large scale channel gainand let eachuser be a cluster. Given the cluster threshold,according to the cluster threshold, we can put the clusters whose mutual interference is strong into a cluster. When the minimum interference distance is large, the inter cluster interference can be neglected, then wecan make each clusteroptimal in energy efficiency in order to achieve sub-optimal of the whole system in energy efficiency. Furthermore, we can furtherimprove the energy efficiency performance of the system through the adaptive adjustment of the cluster threshold.Chapter 5 summarizes the research work of this article, and gives the direction of this research can be extended.