Cited By
View all- Fraz MMuslam MHussain MAmin RXie J(2023)Smart sensing enabled dynamic spectrum management for cognitive radio networksFrontiers in Computer Science10.3389/fcomp.2023.12718995Online publication date: 19-Dec-2023
Spectrum Handoff Based on Bilateral Auction Mechanism in Centralized Cognitive Radio Networks
Authors: 
Yunfei Peng, Wei Shao, Chunlan Lu, Shufeng Li, Guanjie Wang, Peicong HuAuthors Info & Claims
Pages 103 - 107
Abstract
With the exponential explosion of radio services, spectrum scarcity has become a thorny issue in wireless communications. Cognitive radio networks (CRNs) emerge as the times require. However, choosing the best channel for spectrum handoff becomes a challenge faced by cognitive radio networks. Game theory is an important tool to study the interaction between multiple decision makers. In this paper, a spectrum handoff optimization scheme for cognitive radio networks based on auction theory is studied, and a centralized spectrum auction algorithm based on bilateral auction mechanism (BAM) is proposed. Simulation results show that the proposed scheme is effective to select the best channel for spectrum handoff, which improves the system throughput.
References
[1]
H. Khaled, I. Ahmad, D. Habibi and Q. V. Phung. A Secure and Energy-Aware Approach For Cognitive Radio Communications, in IEEE Open Journal of the Communications Society, vol. 1, pp. 900-915, 2020, https://
[2]
G. Rathee, N. Jaglan, S. Garg, B. J. Choi and K. -K. R. Choo, A Secure Spectrum Handoff Mechanism in Cognitive Radio Networks, in IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 3, pp. 959-969, Sept. 2020, https://
[3]
X. Gao, P. Wang, D. Niyato, K. Yang and J. An, Auction-Based Time Scheduling for Backscatter-Aided RF-Powered Cognitive Radio Networks, in IEEE Transactions on Wireless Communications, vol. 18, no. 3, pp. 1684-1697, March 2019, https://
[4]
T. N. Tran, T. -V. Nguyen, K. Shim and B. An, A Game Theory Based Clustering Protocol to Support Multicast Routing in Cognitive Radio Mobile Ad Hoc Networks, in IEEE Access, vol. 8, pp. 141310-141330, 2020, https://
[5]
R. Fan, W. Chen, H. Jiang, J. An, K. Yang and C. Xing, Dynamic Spectrum Leasing With Two Sellers, in IEEE Transactions on Vehicular Technology, vol. 67, no. 6, pp. 4852-4866, June 2018, https://
[6]
F. Li, K. Lam, X. Li, X. Liu, L. Wang and V. C. M. Leung, Dynamic Spectrum Access Networks With Heterogeneous Users: How to Price the Spectrum?, in IEEE Transactions on Vehicular Technology, vol. 67, no. 6, pp. 5203-5216, June 2018, https://
[7]
H. Chang and K. Chen, Auction-Based Spectrum Management of Cognitive Radio Networks, in IEEE Transactions on Vehicular Technology, vol. 59, no. 4, pp. 1923-1935, May 2010, https://
[8]
W. Zhou, T. Jing, Y. Huo, J. Qian and Z. Li, Double Auction for Joint Channel and Power Allocation in Cognitive Radio Networks, in The Computer Journal, vol. 58, no. 12, pp. 3295-3305, Dec. 2015, https://
[9]
C. Yi and J. Cai, Two-Stage Spectrum Sharing With Combinatorial Auction and Stackelberg Game in Recall-Based Cognitive Radio Networks, in IEEE Transactions on Communications, vol. 62, no. 11, pp. 3740-3752, Nov. 2014, https://
[10]
G. Sun, Coalitional Double Auction for Spatial Spectrum Allocation in Cognitive Radio Networks, in IEEE Transactions on Wireless Communications, vol. 13, no. 6, pp. 3196-3206, June 2014, https://
[11]
X. Zhai, T. Zhou, C. Zhu, B. Chen, W. Fang and K. Zhu, Truthful Double Auction for Joint Internet of Energy and Profit Optimization in Cognitive Radio Networks, in IEEE Access, vol. 6, pp. 23180-23190, 2018, https://
[12]
M. Aggarwal, T. Velmurugans, M. Karuppiah, M. M. Hassan, A. Almogren and W. N. Ismail, Probability-Based Centralized Device for Spectrum Handoff in Cognitive Radio Networks, in IEEE Access, vol. 7, pp. 26731-26739, 2019, https://
[13]
C. Wu, Y. Wang and Z. Yin, Realizing Railway Cognitive Radio: A Reinforcement Base-Station Multi-Agent Model, in IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 4, pp. 1452-1467, April 2019, https://
[14]
A. O. Bicen, E. B. Pehlivanoglu, S. Galmes and O. B. Akan, Dedicated Radio Utilization for Spectrum Handoff and Efficiency in Cognitive Radio Networks, in IEEE Transactions on Wireless Communications, vol. 14, no. 9, pp. 5251-5259, September 2015, https://
[15]
W. Yin and H. Chen, Decision-Driven Time-Adaptive Spectrum Sensing in Cognitive Radio Networks, in IEEE Transactions on Wireless Communications, vol. 19, no. 4, pp. 2756-2769, April 2020, https://
[16]
K. A.M., J. D. Matyjas, F. Hu and S. Kumar, Channel/Beam Handoff Control in Multi-Beam Antenna Based Cognitive Radio Networks, in IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 1, pp. 30-42, March 2018, https://
[17]
S. Kamiya, K. Nagashima, K. Yamamoto, T. Nishio, M. Morikura and T. Sugihara, Performance evaluation of overlap mitigation through spatial adaptive play for dense wlans, 2015 21st Asia-Pacific Conference on Communications (APCC), 2015, pp. 386-390, https://
Recommendations
Spectrum handoff in cognitive radio networks
The rapid progression in wireless networking has raised the demand of extra spectrum bands. The current fixed spectrum allocation policy used by the government agencies is unable to accommodate the growing demand of the wireless networks. The research ...
Joint spectrum load balancing and handoff management in cognitive radio networks: a non-cooperative game approach
We propose a non-cooperative game theory based algorithm for spectrum management problem in cognitive radio networks taking into account the spectrum handoff effects. The objective is to minimize the spectrum access time of Secondary Users (SUs) which ...
Spectrum handoff in cognitive radio networks: opportunistic and negotiated situations
ICC'09: Proceedings of the 2009 IEEE international conference on CommunicationsSpectrum handoff is an indispensable component in cognitive radio networks to provide resilient service for the secondary users. In this paper, we explore the spectrum handoff procedure and then propose four metrics to characterize both short-term and ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
December 2021
146 pages
ISBN:9781450385848
DOI:10.1145/3510513
Copyright © 2021 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]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 10 May 2022
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ICNCC 2021
ICNCC 2021: 2021 The 10th International Conference on Networks, Communication and Computing
December 10 - 12, 2021
Beijing, China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 27Total Downloads
- Downloads (Last 12 months)9
- Downloads (Last 6 weeks)0
Reflects downloads up to 23 Sep 2024
Other Metrics
Citations
Cited By
View all- Fraz MMuslam MHussain MAmin RXie J(2023)Smart sensing enabled dynamic spectrum management for cognitive radio networksFrontiers in Computer Science10.3389/fcomp.2023.12718995Online publication date: 19-Dec-2023
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format