DocumentCode
3485036
Title
Applying genetic algorithms to the data traffic scheduling and performance analysis of a long-term evolution system
Author
Hsien-Wei Tseng ; Yang-Han Lee ; Wei-Chen Lee ; Yih-Guang Jan ; Chorng-Ren Sheu
Author_Institution
Dept. of Comput. & Commun. Eng., De Lin Inst. of Technol., Taipei, Taiwan
fYear
2012
fDate
4-7 Nov. 2012
Firstpage
183
Lastpage
188
Abstract
This study developed a superior transmission resource allocation method using genetic algorithms. The convergence properties of genetic algorithms were employed to increase the transmission resource use efficiency of a base station, allowing users to access wider bandwidths and improving the system throughput and packet service rates of a multicarrier operation. This study also determined the genetic algorithm convergence time and found that the convergence time required for actual calculation was significantly less than one radio frame duration. Finally, the resource allocation results were simulated with and without the genetic algorithm to compare the performance differences.
Keywords
Long Term Evolution; convergence; genetic algorithms; resource allocation; scheduling; telecommunication traffic; bandwidths; convergence property; data traffic scheduling; genetic algorithm convergence time; genetic algorithms; long-term evolution system; multicarrier operation; packet service rates; performance analysis; radio frame duration; superior transmission resource allocation method; system throughput; transmission resource use efficiency; Biological cells; Convergence; Genetic algorithms; Long Term Evolution; Resource management; Throughput; Time frequency analysis; Genetic algorithm; multicarrier operation; resource allocation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Signal Processing and Communications Systems (ISPACS), 2012 International Symposium on
Conference_Location
New Taipei
Print_ISBN
978-1-4673-5083-9
Electronic_ISBN
978-1-4673-5081-5
Type
conf
DOI
10.1109/ISPACS.2012.6473477
Filename
6473477
Link To Document