DocumentCode :
3574142
Title :
Energy-efficient subcarrier-bit-power allocation based on genetic algorithm
Author :
Congcong Li ; Guixia Kang ; Ningbo Zhang ; Dongyan Huang ; Xiaoshuang Liu ; Bingning Zhu ; Hao Wu
Author_Institution :
Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2014
Firstpage :
583
Lastpage :
588
Abstract :
Energy-efficient transmission is an important issue for wireless communication systems, due to the increased energy consumption and limited battery capacity. In this paper, we study the energy-efficient transmission in a single cellular downlink multi-user Orthogonal Frequency Division Multiple Access (OFDMA) system. The transmit power consumption and the circuit power consumption are both taken into consideration, when optimizing the total bits transmitted per Joule of energy. This optimization problem has nonlinear constraints, which are commonly solved by Lagrange-based algorithm. However, these methods are time-consuming and are not optimal. To address this issue, we propose an adaptive subcarrier, bit, and power allocation scheme to optimize energy-efficient transmissions based on genetic algorithms. Moreover, we improve the genetic algorithm with a new elitist method and a penalty handling method that are specific to our optimization problem. The simulation results show that the proposed scheme can obtain more satisfied solutions in a shorter time, compared to the traditional methods.
Keywords :
OFDM modulation; cellular radio; frequency division multiple access; genetic algorithms; multiuser channels; power consumption; telecommunication power management; wireless channels; Lagrange based algorithm; OFDMA system; energy-efficient subcarrier-bit-power allocation; energy-efficient transmission; genetic algorithm; multiuser orthogonal frequency division multiple access; nonlinear constraints; penalty handling method; power consumption; single cellular downlink; wireless communication systems; Energy efficiency; Genetic algorithms; OFDM; Optimization; Power demand; Resource management; Wireless communication; Energy-efficiency; Genetic Algorithm; Multi-user; OFDMA; Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications and Networking in China (CHINACOM), 2014 9th International Conference on
Type :
conf
DOI :
10.1109/CHINACOM.2014.7054363
Filename :
7054363
Link To Document :
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