By Topic

Multi-objective Optimization of Power Control and Resource Allocation for Cognitive Wireless Networks

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
$33 $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

4 Author(s)
Yujun Bao ; Inf. Inst., Southwest Univ. of Sci. & Technol., Mian Yang, China ; Hong Jiang ; Yuqing Huang ; Rongchun Hu

Resource optimization is a very important aspect in cognitive radio network (CRN). It is a typical multi-objective optimization problem. This paper proposes a mixed multi-objective immune cloning genetic algorithm (MMGA) to solve the optimization of resource allocation in CRNs. Based on the genetic algorithm of non-domination sort, the MMGA adds external memory immune operator and cloning operator to effectively improve the searching performance. To evaluate the performance of MMGA, we compare it to NSGA-II with three typical test functions. From the results, the MMGA can solve multi-objective optimization problems more effectively than the NSGA-II. Simultaneously, the MMGA is used to optimize the frequency bandwidths and bandwidth-footprint product in CRNs. The simulation results show that MMGA can effectively solve the optimization of resource allocation in CRNs.

Published in:

Computer and Information Science, 2009. ICIS 2009. Eighth IEEE/ACIS International Conference on

Date of Conference:

1-3 June 2009