Cited By
View all- Kulshrestha RSingh A(2024)Transient analysis of energy-saving strategy for cognitive radio networks using G-queue with heterogeneityComputer Communications10.1016/j.comcom.2024.01.007216(295-306)Online publication date: Feb-2024
Multiple Sleep Mode Analysis for Energy Conservation in Green Cognitive Radio Networks
Authors: 
Jianping Liu, Shunfu Jin, Wuyi YueAuthors Info & Claims
Article No.: 9, Pages 1 - 6
Abstract
In this paper, we examine the key issue of how to conserve the energy of base stations (BSs) in "green" Cognitive Radio Networks (CRNs). In order to meet the demand for more sustainable green communication, we introduce a multiple sleep mode for licensed channels in CRNs. Based on a dynamic spectrum access strategy with a proposed multiple sleep mode, we establish a continuous-time Markov Chain model to capture the stochastic behavior of secondary user (SU) and primary user (PU) packets. By using the matrix geometric solution method, we obtain the steady-state probability distribution for the system model. This document also presents analysis for performance evaluation in terms of the average latency of SU packets and the energy saving rate of the system.
References
[1]
J. Marinho and E. Monteiro, Cognitive radio: Survey on communication protocols, spectrum decision issues, and future research directions. Wireless Networks, vol. 18, no. 2, pp. 147--164, 2012.
[2]
M. Yang, Y. Li and J. Yuan, Opportunistic spectrum sharing based resource allocation for wireless virtualization, Proceedings of the International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, pp. 51--58, 2013.
[3]
K. Kim, T-preemptive priority queue and its application to the analysis of an opportunistic spectrum access in cognitive radio networks, Computers and Operations Research, vol. 39, no. 7, pp. 1394--1401, 2012.
[4]
X. Huang, T. Han and N. Ansari, Green energy powered cognitive radio networks, IEEE Communications Surveys and Tutorials, vol. 17, no. 2, pp. 827--842, 2015.
[5]
X. Wu, J. Xu, M. Chen and J. Wang, Optimal energy-efficient sensing in cooperative cognitive radio networks, Eurasip Journal on Wireless Communications and Networking, vol. 2014, no. 1, pp. 25--28, 2014.
[6]
C. Yang, M. Sheng and J. Li, Energy-aware joint power and rate control in overlay cognitive radio networks: A NASH bargaining perspective, Proceedings of the 4th International Conference on Intelligent Networking and Collaborative Systems, pp. 520--524, 2012.
[7]
L. Wang, M. Sheng and Y. Zhang, Robust energy efficiency maximization in cognitive radio networks: The worst-case optimization approach, IEEE Transactions on Communications, vol. 63, no. 1, pp. 51--65, 2015.
[8]
Y. Qu, M. Wang and J. Hu, A new energy-efficient scheduling algorithm based on particle swarm optimization for cognitive radio networks, Proceedings of the 14th International Conference on Signal Processing, Communications and Computing, pp. 813--821, 2014.
[9]
Y. Teng and H. Xu, An energy efficiency heuristic algorithm for joint optimization in cognitive radio networks, Proceedings of IEEE International Conference on Communications Workshops, pp. 469--473, 2013.
[10]
M. Rashid, M. Hossain and E. Hossain, Opportunistic spectrum scheduling for multiuser cognitive radio: A queueing analysis, IEEE Transactions on Wireless Communications, vol. 8, no. 10, pp. 5259--5269, 2009.
[11]
J. Qiao, J. Liu and W. Wang, Spectrum-driven sleep scheduling algorithm based on reliable theory in cognitive radio sensor networks, Journal of China Universities of Posts and Telecommunications, vol.19, no. SUPPL. 2, pp. 47--51+72, 2012.
[12]
Y. Chen, N. Wang, Y. Shih and J. Lin, Improving low-energy adaptive clustering hierarchy architectures with sleep mode for wireless sensor networks, Wireless Personal Communications, vol. 75, no. 1, pp. 349--368, 2014.
[13]
G. Wu, L. Dong, Z. Qin and Z. Xu, Dynamic programming-based pico base station sleep mode control in heterogeneous networks, International Journal of Communication Systems, vol. 27, no. 11, pp. 2697--2980, 2014.
[14]
Y. Xiao, S. Zhang and J. Cao, An energy-preserving spectrum access strategy in cognitive radio networks, Proceedings of IEEE Wireless Communications and Networking Conference, pp. 738--743, 2013.
Recommendations
Towards energy-efficient cooperative spectrum sensing for cognitive radio networks: an overview
Cognitive radio has been proposed as a promising technology to resolve the spectrum scarcity problem by dynamically exploiting underutilized spectrum bands. Cognitive radio technology allows unlicensed users to exploit the spectrum vacancies at any time ...
Green-Energy-Powered Cognitive Radio Networks: Joint Time and Power Allocation
Special Issue on Autonomous Battery-Free Sensing and Communication, Special Issue on ESWEEK 2016 and Regular PapersThis article studies a green-energy-powered cognitive radio network (GCRN) in an underlay paradigm, wherein multiple battery-free secondary users (SUs) capture both the spectrum and the energy of primary users (PUs) to communicate with an access point (...
Optimal Mode Selection Policies in Cognitive Radio Networks with RF Energy Harvesting
Applying energy harvesting technology in cognitive radio networks (CRNs) leads to a tradeoff between the time allocated for spectrum sensing followed by spectrum accessing and that for energy harvesting. This tradeoff can be formulated as a mode ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
December 2016
159 pages
ISBN:9781450348423
DOI:10.1145/3016032
Copyright © 2016 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
In-Cooperation
- SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
- Victoria University of Wellington
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 December 2016
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
Conference
QTNA '16
QTNA '16: 11th International Conference on Queueing Theory and Network Applications
December 13 - 15, 2016
Wellington, New Zealand
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 51Total Downloads
- Downloads (Last 12 months)8
- Downloads (Last 6 weeks)2
Reflects downloads up to 16 Nov 2024
Other Metrics
Citations
Cited By
View all- Kulshrestha RSingh A(2024)Transient analysis of energy-saving strategy for cognitive radio networks using G-queue with heterogeneityComputer Communications10.1016/j.comcom.2024.01.007216(295-306)Online publication date: Feb-2024
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in