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

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/107468

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107468

Title:	Ultra-dense small cell planning using cognitive radio network toward 5G
Authors:	周立德;Tseng, Fan-hsun;Chou, Li-der;Chao, Han-chieh;Wang, Jin
Contributors:	資訊電機學院資訊工程學系
Keywords:	5G mobile communication;Cognitive radio;Computer architecture;Interference;Macrocell networks;Microprocessors;Software defined radio
Date:	2015-12-01
Issue Date:	2026-04-23 14:13:53 (UTC+8)
Publisher:	Institute of Electrical and Electronics Engineers Inc.;IEEE
Abstract:	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 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. 其他題名： WC-M 出版者： IEEE 出版日期： 2015-12 出處： IEEE wireless communications, 2015-12, Vol.22 (6), p.76-83 資源來源： IEEE Xplore 識別號： ISSN: 1536-1284 識別號： DOI: 10.1109/MWC.2015.7368827 識別號： CODEN: IWCEAS
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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