ULTRA-DENSE SMALL CELL PLANNING USING COGNITIVE RADIO NETWORK TOWARD 5G

被引:62
|
作者
Tseng, Fan-Hsun [1 ]
Chou, Li-Der [1 ]
Chao, Han-Chieh [2 ,3 ]
Wang, Jin [4 ]
机构
[1] Natl Cent Univ, Taipei, Taiwan
[2] Natl Ilan Univ, Natl Dong Hwa Univ, Nanjing Univ Informat Sci & Technol, Yilan 260, Taiwan
[3] Fujian Univ Technol, Fuzhou, Peoples R China
[4] Yangzhou Univ, Yangzhou 225009, Jiangsu, Peoples R China
关键词
Cognitive radio - Cells - Cytology - Signal to noise ratio - Network architecture - Radio interference - Spectrum efficiency - Frequency allocation;
D O I
10.1109/MWC.2015.7368827
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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 graph-based) 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 ultra-dense 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 graph-based algorithm. Finally, we conclude this article by discussing potential challenges and opportunities.
引用
收藏
页码:76 / 83
页数:8
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