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Wideband Sensing for Cognitive Radio Systems in Heterogeneous Next Generation Networks
Ahmed M. Barnawi
Pages - 135 - 150     |    Revised - 01-05-2011     |    Published - 31-05-2011
Volume - 3   Issue - 2    |    Publication Date - May / June 2011  Table of Contents
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KEYWORDS
Cognitive Radio, Interference Characterization., Spectrum Sensing
ABSTRACT
Mobile Next Generation Network (MNGN) is characterized as heterogeneous network where variety of access technologies are meant to coexist. Decisions on choosing an air interface that meets a particular need at a particular time will be shifted from the network’s side to (a more intelligent) user’s side. On top of that network operators and regularities have come to the realization that assigned spectrum bands are not utilized as they should be. Cognitive radio stands out as a candidate technology to address many emerging issues in MNGN such as capacity, quality of service and spectral efficiency. As a transmission strategy, cognitive radio systems depend greatly on sensing the radio environment. In this paper, we present a novel approach for interference characterization in cognitive radio networks based on wideband chirp signal. The results presented show that improved sensing accuracy is maintained at tolerable system complexity.
CITED BY (11)  
1 Verma, V., & Baghla, S. Performance Evaluation of QoS in WLAN-UMTS Network Using OPNET Modeller.
2 Zayaraz, G., Devi, J. K., Vijayalakshmi, V., & Hemamalini, V. Mobility management in heterogeneous wireless networks.
3 Kumar, D., Jolly, A., & Kumar, S. N. Performance Of Integrated Heterogeneous Network (WLAN-SGSN AND WLAN-GGSN).
4 Tripathi, S., & Jain, A. K. (2014). Research Issues in UMTS-WLAN Interworking: A Survey. Journal of Mobile Computing, Communications & Mobile Networks, 1(3), 34-41.
5 Aziz, A., & Saad, N. M. (2014, June). Load and service adaptive algorithm (LSAA) for tight coupling based integration architecture. In Intelligent and Advanced Systems (ICIAS), 2014 5th International Conference on (pp. 1-5). IEEE.
6 Chakraborty, N. (2013). Performance analysis of economic model and radio resource management in heterogeneous wireless networks. International Journal of Computer Networks & Communications, 5(5), 183.
7 Singh, H. P., & Bala, M. (2013). Evaluation of Integrated WiMAX-WLAN under Pervasive Environment in OPNET. International Journal of Computer Applications, 82(17).
8 Vijayalakshmy, G., & Sivaradje, G. (2014). Loosely coupled heterogeneous networks convergence using IMS-SIP-AAA. International Journal of Computer Applications, 85(16).Nganya, G. C., Joseph, G. M., Echegini, N. S., & Nwankwo, E. L. (2016). Achieving a Seamless Mobility in the 3G and WLAN Networks Integration when the WLAN AP is Tightly Coupled to the SG
9 Mu, D., Ge, X., & Chai, R. (2013, October). Vertical handoff modeling and simulation in VANET scenarios. In Wireless Communications & Signal Processing (WCSP), 2013 International Conference on (pp. 1-6). IEEE.
10 Rizvi, S., & Saad, N. M. (2014, June). A multi-homing seamless vertical handoff protocol for integrated UMTS/WLAN network. In Intelligent and Advanced Systems (ICIAS), 2014 5th International Conference on (pp. 1-6). IEEE.
11 Hamada, R. A., Ali, H. S., & Abdalla, M. I. (2014). SIP-based mobility management for LTE-WiMAX-WLAN interworking using IMS architecture. Int J Comput Netw (IJCN), 6(1), 1-14.Kim, H. S., Kim, E., & Kim, H. (2012, June). QoE-driven Wi-Fi selection mechanism for next generation smartphones. In Enabling Technologies for Smartphone and Internet of Things (E
1 Google Scholar 
2 Google Scholar 
3 CiteSeerX 
4 refSeek 
5 iSEEK 
6 Scribd 
7 SlideShare 
8 PdfSR 
A. Barnawi, “Adaptive Technologies for Hybrid Ad hoc/Cellular Network Architecture," to appear in International Journal on Ad hoc and Ubiquitous Computing (IJAHUC), May 2011.
A. Ben Salem, M. Siala and H. Boujemaa, “Performance Comparsion of OFDMA and OFDM/OQAM Systems Operating in Highly Time and Frequency Dispersive Radio Mobile Channels.” in Proceedings of the IEEE International Conference on Electronics, Circuit and Systems, Gammarth, 2005
A. Sahai and D. Cabric, “A tutorial on spectrum sensing: Fundamental limits and practical challenges,” in Proceedings of IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, MD, 2005.
“FCC September Commission Meeting Presentation,” September 29,(2009).
D. Cabric, S.M. Mishra, R. W. Brodersen, “Implementation Issues in Spectrum Sensing for Cognitive Radios.” In Proceedings of the 38th Annual Asilomar Conference on Signals,Systems and Computers, 2004
Federal Communications Commission, “Notice of proposed rulemaking and order: Facilitating opportunities for flexible, efficient, and reliable spectrum use employing cognitive radio technologies,” ET Docket No. 03-108, February 2005.
H. J. Wang, R. H. Katz, and J. Giese, “Policy-enabled handoffs across heterogeneous wireless networks.” In Proceedings of IEEE Workshop on Mobile Computing Systems and Applications, 1999.
K-C Chen and R. Prasad , “Cognitive Radio Networks” John Wiley & Sons Ltd, pp. 183-186, (2009)
L. Huang, Y. Lu and W. Liu, “Using Chirp Signal for Accurate RFID Positioning.” In Proceedings of the International Conference on Communications, Circuit and Systems (ICCCAS), Chengdu, China, 2010.
M. M. Buddhikot, “Cognitive Radio, DSA and Self-X: Towards Next Transformation in Cellular Networks.” In Proceedings of 2010 IEEE Symposium on New Frontiers in Dynamic Spectrum, 2010
M. R. Winkley, “Chirp signals for communications.” In the Proceedings of the IEEE WESCON conference, 1962.
R. J. Haines, “Cognitive Pilot Channels for Femto-cell Deployment.” in Proceedings of the 7th International Symposium on Wireless Communication Systems (ISWCS), York, UK,2010
S. Hussain and X. Fernando, “Spectrum Sensing in Cognitive Radio Networks: Up-to-date Techniques and Future Challenges,” In Proceedings of the IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH), Toronto, Canada, 2009.
T. Yucek and H. Arslan, “Spectrum Characterization for Opportunistic Cognitive Radio Systems In Proceedings of IEEE MILCOM 2006, 2006.
T. Yucek. and H. Arslan, “A survey of spectrum sensing algorithms for cognitive radio applications.”, IEEE journal for Communications Surveys & Tutorials, 11 (1), 2009
W. A. Gardner, C. M. Spooner, “Signal Interception: Performance advantages of Cyclicfeature detectors”, IEEE Transaction on Communications, vol. 40, January 1992.
X. Chen L and Zhao J Li, “A Modified Spectrum Sensing Methods for Widband Cognitive Radio Based on Compressive Sensing.” In Proceedings of the 4th International Conference on Networking in China, Xian, China, 2009.
Y. Hur, J. Park, W. Woo, K. Lim, C.-H. Lee, H. S. Kim, and J. Laskar, “A wideband analog multi-resolution spectrum sensing technique for cognitive radio systems.” In the Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS), Island of Kos, Greece, 2006
Z. Quan, S Cui, V. Poor, “Wideband Spectrum Sensing in Cognitive Radio Networks.” In Proceedings of IEEE International Conference on Communications, Beijing, China, 2008.
Z. Tian and G. B. Giannakis, “A wavelet approach to wideband spectrum sensing for cognitive radios.” In Proceedings of the 1st Int. Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Mykonos Island, Greece, 2006.
Mr. Ahmed M. Barnawi
- Saudi Arabia
ambarnawi@kau.edu.sa


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