Research On Energy Efficiency Optimization For Distributed Antenna Systems

With the rapidly development of mobile communication technology, a high quality com-munication experience with high speed and multiple services has been available for everyone. Meanwhile, the energy consumption of communication systems increase dramatically. Thus, it is a strong impetus for the development of green communication whose aim is to decrease system’s energy consumption and increase system’s energy efficiency. The distributed antenna system (DAS) is regarded as an indispensable part of green communication duo to its advantages of deploying flexibly, shortening the distance between users and distributed antennas (DA). This paper mainly focus on the power allocation algorithm and DA deployment strategy to maximize energy efficiency in DAS. In order to establish the theoretical basis, wireless channel theory, including large-scale fading and small-scale fading, is described in this paper. What is more, the structure of DAS and the system capacity in downlink DAS have been analysed in this pa-per. And then, the popular metric of energy efficiency and the energy consumption model are established.The energy efficiency maximization for single-user DAS is investigated in this paper. The optimization problem aiming at maximizing energy efficiency is formulated with the restrict-ed conditions. In order to solve the optimization problem, several lemmas and theorem are introduced. Thus, a two step optimization algorithm which the first is to find the optimal num-ber of DA and the second is to calculate the power allocation with help of Lambert function is obtained. Compared with the traditional power allocation algorithm which requires iterative Lambert function calculations, the computation complexity is greatly reduced. Simulation re-sults demonstrate that the proposed algorithm has no performance degradation compared with computer exhaustive search.The antenna location in DAS with hybrid user distribution is discussed in this paper. In order to distinguish different types of users, the weighted power allocation factor is adopted. The DA deployment problem is builded with the distribution of users. Moreover, the weight-ed expectation of squared distance criterion derived from the unweighted one is considered to solve the problem. Consequently, a closed form solution in polar coordinates can be attained. Meanwhile, the optimal transmission power allocation among DAs to achieve the maximum energy efficiency is proved to be unique. Simulation results illustrate that the energy efficiency obtained with the proposed method is approximate to computer search result and outperforms the equal power allocation.This paper investigates the power allocation for energy efficiency maximization in DAS constrained by the hybrid minimum rate requirement. The optimization problem maximizing energy efficiency is proved to be non-convex. However, an equivalent convex optimization problem can be obtained from the original problem with the assistance of nonlinear fractional programming. Thus, an iterative power allocation algorithm can be derived by solving its trans-formational problem in its dual domain. Furthermore, the proposed algorithm converge to the global optimal energy efficiency. Simulation results not only confirm the convergence of the proposed algorithm but also demonstrate a better performance than the traditional rate adaptive power allocation scheme.