Ultra-dense small cell planning using cognitive radio network toward 5G

Fan Hsun Tseng, Li Der Chou, Han Chieh Chao, Jin Wang

Research output: Contribution to journalArticlepeer-review

66 Scopus citations

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 reconfgurable 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.

Original languageEnglish
Article number7368827
Pages (from-to)76-83
Number of pages8
JournalIEEE Wireless Communications
Volume22
Issue number6
DOIs
StatePublished - Dec 2015

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