DocumentCode :
3612835
Title :
Ultra-dense small cell planning using cognitive radio network toward 5G
Author :
Tseng, Fan-hsun ; Chou, Li-der ; Chao, Han-chieh ; Wang, Jin
Author_Institution :
National Central University
Volume :
22
Issue :
6
fYear :
2015
fDate :
12/1/2015 12:00:00 AM
Firstpage :
76
Lastpage :
83
Abstract :
Mobile communication is facing new challenges to the soaring traffic demand of numerous user devices; thus, the notion of the small cell has been proposed and realized in recent years. However, licensed spectrum has been occupied by various underlying access technologies, so the deployment of small cells needs a sophisticated planning algorithm. In this article, we provide an overview of reconfigurable radio and small cell technologies, then introduce the tentative network architecture for 5G. Two planning approaches (i.e., genetic-based and graphbased) are proposed that accommodate cognitive radio technology to improve user throughput by eliminating communication interference. Since cognitive radio networking provides frequency allocation with cognition cycle for better spectral efficiency, we tackle the deployment of ultradense small cells and consider the coordination of unlicensed spectrum at the same time. Results show that the proposed algorithms with spectrum cognition improve network performance in terms of throughput and signal-to-interference- plus-noise ratio. Specifically, the genetic- based algorithm increases 232 percent in throughput and 150 percent in signal-to-interference- plus-noise ratio compared to the graphbased algorithm. Finally, we conclude this article by discussing potential challenges and opportunities.
Keywords :
5G mobile communication; Cognitive radio; Computer architecture; Interference; Macrocell networks; Microprocessors; Software defined radio;
fLanguage :
English
Journal_Title :
Wireless Communications, IEEE
Publisher :
ieee
ISSN :
1536-1284
Type :
jour
DOI :
10.1109/MWC.2015.7368827
Filename :
7368827
Link To Document :
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