Cart (Loading....) | Create Account
Close category search window
 

Adaptive resource allocation based on modified Genetic Algorithm and Particle Swarm Optimization for multiuser OFDM systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ahmed, I. ; Dept. of Electr. & Electron. Eng., Bangladesh Univ. of Eng. & Technol., Dhaka ; Majumder, S.P.

Adaptive resource allocation is one of the most challenging tasks for multiuser orthogonal frequency division multiplexing (OFDM) systems. In this paper, two evolutionary approaches, genetic algorithm (GA) and particle swarm optimization (PSO) have been applied for adaptive subcarrier and bit allocations to minimize the overall transmit power of a multiuser OFDM system. Each user will be assigned a number of subcarriers with at least one minimum subcarrier even at the worst case. Then the number of bits and the transmit power level for each subcarrier are calculated. Simulation results show that both the evolutionary approaches outperform the conventional static resource allocation schemes considerably in multiuser scenario. The results further reveal that both the algorithms can handle large allocation of subcarriers without significant performance degradation. However the performance of PSO is found to be better than the GA in terms of execution time, simplicity and convergence.

Published in:

Electrical and Computer Engineering, 2008. ICECE 2008. International Conference on

Date of Conference:

20-22 Dec. 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.