The Community for Technology Leaders
RSS Icon
Issue No.02 - February (2011 vol.10)
pp: 161-174
Won-Yeol Lee , Georgia Institute of Technology, Atlanta
Ian F. Akyildiz , Georgia Institute of Technology, Atlanta
Cognitive radio networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face to a unique challenge based on the fluctuating nature of heterogeneous spectrum bands as well as the diverse service requirements of various applications. In this paper, a spectrum decision framework is proposed to determine a set of spectrum bands by considering the application requirements as well as the dynamic nature of spectrum bands. To this end, first, each spectrum is characterized by jointly considering primary user activity and spectrum sensing operations. Based on this, a minimum variance-based spectrum decision is proposed for real-time applications, which minimizes the capacity variance of the decided spectrum bands subject to the capacity constraints. For best-effort applications, a maximum capacity-based spectrum decision is proposed where spectrum bands are decided to maximize the total network capacity. Moreover, a dynamic resource management scheme is developed to coordinate the spectrum decision adaptively dependent on the time-varying cognitive radio network capacity. Simulation results show that the proposed methods provide efficient bandwidth utilization while satisfying service requirements.
Cognitive radio networks, spectrum decision, spectrum characterization, real-time application, best-effort application, minimum variance-based spectrum decision, maximum capacity-based spectrum decision, resource management.
Won-Yeol Lee, Ian F. Akyildiz, "A Spectrum Decision Framework for Cognitive Radio Networks", IEEE Transactions on Mobile Computing, vol.10, no. 2, pp. 161-174, February 2011, doi:10.1109/TMC.2010.147
[1] I.F. Akyildiz, W.-Y. Lee, M.C. Vuran, and S. Mohanty, "A Survey on Spectrum Management in Cognitive Radio Networks," IEEE Comm. Magazine, vol. 46, no. 4, pp. 40-48, Apr. 2008.
[2] D. Cabric, S.M. Mishra, and R.W. Brodersen, "Implementation Issues in Spectrum Sensing for Cognitive Radios," Proc. IEEE Asilomar Conf. Signals, Systems and Computers, pp. 772-776, Nov. 2004.
[3] D. Cabric, S.M. Mishra, D. Willkomm, R. Brodersen, and A. Wolisz, "A Cognitive Radio Approach for Usage of Virtual Unlicensed Spectrum," Proc. 14th IST Mobile and Wireless Comm. Summit, June 2005.
[4] L. Cao and H. Zheng, "Distributed Spectrum Allocation via Local Bargaining," Proc. IEEE Sensor and Ad Hoc Comm. and Networks (SECON), pp. 475-486, Sept. 2005.
[5] L. Cao and H. Zheng, "Distributed Rule-Regulated Spectrum Sharing," IEEE J. Selected Areas in Comm., vol. 26, no. 1, pp. 130-145, Jan. 2008.
[6] C. Chou, S. Shankar, H. Kim, and K.G. Shin, "What and How Much to Gain by Spectrum Agility?" IEEE J. Selected Areas in Comm., vol. 25, no. 3, pp. 576-588, Apr. 2007.
[7] R. Etkin, A. Parekh, and D. Tse, "Spectrum Sharing for Unlicensed Bands," IEEE J. Selected Areas in Comm., vol. 25, no. 3, pp. 517-528, Apr. 2007.
[8] J.R. Evans and E. Minieka, Optimization Algorithms for Networks and Graphs, second ed. CRC Press, 1992.
[9] FCC, ET Docket No 02-135, Spectrum Policy Task Force Report, Nov. 2002.
[10] M. Gandetto and C. Regazzoni, "Spectrum Sensing: A Distributed Approach for Cognitive Terminals," IEEE J. Selected Areas in Comm., vol. 25, no. 3, pp. 546-557, Apr. 2007.
[11] IEEE P802.22/D0.3.8.1, IEEE 802.22 WG, Draft Standard for Wireless Regional Area Networks Part 22: Cognitive Wireless RAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Policies and Procedures for Operation in the TV Bands, IEEE, Sept. 2007.
[12] X. Kang, Y. Liang, A. Nallanathan, H. Garg, and R. Zhiang, "Optimal Power Allocation for Fading Channels in CR Networks: Ergodic Capacity and Outage Capacity," IEEE Trans. Wireless Comm., vol. 8, no. 2, pp. 940-950, Feb. 2009.
[13] W.-Y. Lee and I.F. Akyildiz, "Optimal Spectrum Sensing Framework for Cognitive Radio Networks," IEEE Trans. Wireless Comm., vol. 7, no. 10, pp. 3845-3857, Oct. 2008.
[14] W.-Y. Lee and I.F. Akyildiz, "Spectrum-Aware Mobility Management in Cognitive Radio Cellular Networks," to be published.
[15] Y.C. Liang, Y. Zeng, E. Peh, and A.T. Hoang, "Sensing-Throughput Tradeoff for Cognitive Radio Networks," IEEE Trans. Wireless Comm., vol. 7, no. 4, pp. 1326-1337, Apr. 2008.
[16] N. Nie and C. Comaniciu, "Adaptive Channel Allocation Spectrum Etiquette for Cognitive Radio Networks," Proc. First IEEE Int'l Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN '05), pp. 269-278, Nov. 2005.
[17] C. Peng, H. Zheng, and B.Y. Zhao, "Utilization and Fairness in Spectrum Assignment for Opportunistic Spectrum Access," ACM Mobile Networks and Applications, vol. 11, no. 4, pp. 555-576, Aug. 2006.
[18] M.R. Chari, F. Ling, A. Mantravadi, R. Krishnamoorthi, R. Vijayan, G.K. Walker, and R. Chandhok, "FLO Physical Layer: An Overview," IEEE Trans. Broadcasting, vol. 53, no. 1, pp. 145-159, Mar. 2007.
[19] T. Rappaport, Wireless Communications: Principles and Practice, second ed. Prentice Hall, 2001.
[20] H. Shiang and M. Schaar, "Queuing-Based Dynamic Channel Selection for Heterogeneous Multimedia Applications over Cognitive Radio Networks," IEEE Trans. Multimedia, vol. 5, no. 10, pp. 896-909, Aug. 2008.
[21] K. Sriram and W. Whitt, "Characterizing Superposition Arrival Processes in Packet Multiplexers for Voice and Data," IEEE J. Selected Areas in Comm., vol. 4, no. 6, pp. 833-846, Sept. 1986.
[22] L. Zhang, Y. Liang, and Y. Xin, "Joint Beamforming and Power Allocation for Multiple Access Channels in Cognitive Radio Networks," IEEE J. Selected Areas in Comm., vol. 26, no. 1, pp. 38-51, Jan. 2008.
18 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool