Beamforming and Power Allocation Designs for Energy Efficiency Maximization in MISO Distributed Antenna Systems

In this paper, we present a beamforming and power allocation algorithm for a downlink multiple-input single-output distributed antenna system which maximizes energy efficiency (EE). To reduce the computational complexity of conventional joint optimization approaches relying on an iterative method, w...

Full description

Saved in:
Bibliographic Details
Published in:IEEE communications letters 2013-11, Vol.17 (11), p.2100-2103
Main Authors: Kim, Heejin, Park, Eunsung, Park, Haewook, Lee, Inkyu
Format: Article
Language:English
Subjects:
Antenna arrays
Antennas
Applied sciences
Array signal processing
Detection, estimation, filtering, equalization, prediction
distributed antenna systems
Energy efficiency
Exact sciences and technology
Information, signal and communications theory
Joints
Optimization
Ports (Computers)
Radiocommunications
Resource management
Signal and communications theory
Signal, noise
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we present a beamforming and power allocation algorithm for a downlink multiple-input single-output distributed antenna system which maximizes energy efficiency (EE). To reduce the computational complexity of conventional joint optimization approaches relying on an iterative method, we propose a near optimal scheme based on a closed-form solution. Employing the decomposition property of the joint optimization problem, the EE problem is solved in two steps. First, we determine the beamforming strategy for the EE maximization exposing the structure of beamforming vectors. Then, the optimal power allocation is presented as a closed-form solution by solving Karush-Kuhn-Tucker conditions. Through numerical simulations, we confirm that the proposed solution shows the performance almost identical to the jointly optimum method with much reduced complexity.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2013.100713.131715