NDLI: An energy efficiency scheduling scheme for cognitive radio networks

Content Provider	IEEE Xplore Digital Library
Author	Shami, N. Rasti, M.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Eng. & Inf. Technol., Amirkabir Univ. of Technol. (Tehran Polytech.), Tehran, Iran (Shami, N.; Rasti, M.)
Abstract	In this paper, we focus on operation-modes scheduling in cognitive radio networks (CRNs), in which a cognitive base-station assigns available frequencies to secondary users (SUs). This is formally stated as the problem of maximizing the energy efficiency (defined as the ratio of the total rate of SUs to total energy consumption), which is a nonlinear integer programming, and then present a polynomial time heuristic algorithm to address it. In contrast to existing schemes, in our proposed scheme, the SUs, who do not have any data to transmit or no frequency is assigned to them, transit into the sleep-mode. This would significantly reduce the energy consumption. Furthermore, since SUs consume significant energy during the channel switching, depending on the difference between frequencies of current and new assigned frequencies (i.e, channel switching bandwidth), in our proposed scheme, a new frequency is assigned to SUs if it is at the vicinity of the current frequency. This results in decreased channel switching bandwidth for SUs (which in turn results in decreased energy consumption) and lowered computational overhead. Our simulation results indicate that our algorithm outperforms existing scheduling algorithms for CRNs in terms of energy consumption and the channel switching bandwidth for SUs, without reducing the throughput.
Starting Page	648
Ending Page	653
File Size	881699
Page Count	6
File Format	PDF
e-ISBN	9781479919727
DOI	10.1109/IranianCEE.2015.7146294
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-10
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrical engineering Conferences Frequency assignment Cognitive radio network Energy efficiency Dynamic spectrum management
Content Type	Text
Resource Type	Article

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