The recent phenomena of tremendous growth in wireless communication application urge increasing need of radio spectrum, albeit it being a precious but natural resource. The recent technology under development to overview the situation is the concept of Cognitive Radio (CR). Recently the Artificial Intelligence (AI) tools are being considered for the topic. AI is the core of the cognitive engine that examines the external and internal environment parameters that leads to some postulations for QoS improvement. In this article, we propose a new Artificial Neural Network (ANN) model for detection of a spectrum hole. The model is trained with some pertinent features over a channel like SNR, channel capacity, bandwidth efficiency etc. The channel capacity status could be identified in a quantized index form . Some simulation results are presented.
D. Cabric, S. M. Mishra and R. W. Brodersen, “Implementation Issues in Spectrum Sensing for Cognitive Radio,” Proceedings of 38th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, 7-10 November 2004, pp. 772-776.
I. F. Akyildiz, W. Y. Lee, M. C. Vuran and S. Mohanty, “Next Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey,” International Journal of Computer and Telecommunications Networking, Vol. 50, No. 13, 2006, pp. 2127-2159.
M. Gandetto and C. Regazzoni, “Spectrum Sensing: A Distributed Approach for Cognitive Terminals,” IEEE Journal on Selected Areas in Communications, Vol. 25, No. 3, 2007, pp. 546-557. doi:10.1109/JSAC.2007.070405
M. Subhedar and G. Birajdar, “Spectrum Sensing Techniques in Cognitive Radio Networks: A Survey,” Proceedings of International Journal of Next-Generation Networks, Vol. 3, No. 2, 2011, pp. 37-51.
P. Kolodzy, et al., “Next Generation Communications: Kickoff Meeting,” Proceedings of Defense Advanced Research Projects Agency, Arlington, 17 October 2001.
M. McHenry, “Frequency Agile Spectrum Access Technologies,” FCC Cognitive Radio Workshop, Washington DC, 19 May 2003.
G. Staple and K. Werbach, “The End of Spectrum Scarcity,” IEEE Spectrum, Vol. 41, No. 3, 2004, pp. 48-52. doi:10.1109/MSPEC.2004.1270548
A. Petrin and P. G. Steffes, “Analysis and Comparison of Spectrum Measurements Performed in Urban and Rural Areas to Determine the Total Amount of Spectrum Usage,” Proceeding of 7th Annual ISART, Boulder, 1-3 March 2005.
J. Mitola III and G. Q. Maguire Jr., “Cognitive Radio: Making Software Radios More Personal,” IEEE Personal Communications Magazine, Vol. 6, No. 4, 1999, pp. 13-18.
X. Dong, Y. Li, C. Wu and Y. Cai, “A Learner Based on Neural Network for Cognitive Radio,” 12th IEEE International Conference on Communication Technology, Nanjing, 11-14 November 2010, pp. 893-896.
T. Yucek and H. Arslan, “A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications,” IEEE Communications Surveys & Tutorials, Vol. 11, No. 1, 2009, pp. 116-130. doi:10.1109/SURV. 2009.090109
M. Ghozzi, M. Dohler, F. Marx and J. Palicot, “Cognitive Radio Methods for the Detection of Free Bands,” Comptes Rendus Physique, Vol. 7, No. 7, 2006, pp. 794-804. doi:10.1016/j.crhy.2006.07. 009
J. G. Proakis, “Digital Communications,” McGraw-Hill Pub., New York, 2001.
H. Urkowitz, “Energy Detection of Unknown Deterministic Signals,” Proceedings of the IEEE, Vol. 55, No. 4, 1967, pp. 523-531. doi:10.1109/PROC.1967.5573
F. F. Digham, M. S. Alouini and M. K. Simon, “On the Energy Detection of Unknown Signals over Fading Channels,” IEEE Transactions on Communications, Vol. 55, No. 1, 2007, pp. 21-24. doi:10.1109/TCOMM.2006.887483
I. A. Akbar, K. K. Bae, J.-S. Urn, C. M. Spooner and J. H. Reed, “Cyclostationary Approaches to Signal Detection and Classification in Cognitive Radio,” 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2007), Ireland, 17-20 April 2007, pp. 212-215. doi:10.1109/DYSPAN.2007.35
S. Shankar, C. Cordeiro and K. Challapali, “Spectrum Agile Radios: Utilization and Sensing Architectures,” Proceeding of IEEE International Symposium Ibid, Maryland, 8-11 November 2005, pp. 160-169.
Y. J. Tang, Q. Y. Zhang and W. Lin, “Artificial Neural Network Based Spectrum Sensing Method for Cognitive Radio,” 6th International Conference on Wireless Communications, Networking and Mobile, Chengdu, 23-25 September 2010, pp. 1-4.
S. Pattanayak, P. Venkateswaran and R. Nandi, “Artificial Neural Network for Cognitive Radio: A Preliminery Survey,” WiCOM 2012, Shanghai, 21-23 September 2012.
F. Weidling, D. Datla, V. Petty, P. Krishnan and G. Minden, “A Framework for RF Spectrum Measurements and Analysis,” IEEE International Symposium New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, 8-11 November 2005, pp. 573-576.
D. C. Oh and Y.-H. Lee, “Energy Detection Based Spectrum Sensing for Sensing Error Minimization in Cognitive Radio Networks,” International Journal of Communication Networks and Information Security (IJCNIS), Vol. 1, No. 1, 2009, pp. 1-5.
J. Lehtomaki, J. Vartiainen, M. Juntti and H. Saarnisaari, “Spectrumsensing with forward Methods,” Proceedings of IEEE Military Communications Conference, Washington DC, 23-25 October 2006, pp. 1-7.
J. Vartiainen, H. Sarvanko, J. Lehtomki, M. Juntti and M. Latva-aho, “Spectrum Sensing with LAD-Based Methods,” Proceedings of 18th Annuals of IEEE International Personal, Indoor and Mobile Radio Communications Symposium (PIMRC), Athens, 3-7 September 2007, pp. 1-5.
T. Yücek and H. Arslan, “Spectrum Characterization for Opportunistic Cognitive Radio Systems,” Proceedings of IEEE Military Communications Conference, Washington DC, 23-25 October 2006, pp. 1-6.
D. Cabric and R. W. Brodersen, “Physical Layer Design Issues Unique to Cognitive Radio Systems,” Proceedings of 16th Annuals of IEEE International Personal, Indoor and Mobile Radio Communications Symposium (PIMRC), Vol. 2, Berlin, 11-14 September 2005, pp. 759-763.
J. Proakis, “Digital Communications,” McGraw-Hill, New York, 2001.
Sahai and D. Cabric, “A Tutorial on Spectrum Sensing: Fundamental Limits and Practical Challenges,” Proceeding of IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, 8-11 November 2005.
Y. Zeng and Y. C. Liang, “Spectrum-Sensing Algorithms for Cognitive Radio Based on Statistical Covariances,” IEEE Transactions on Vehicular Technology, Vol. 58, No. 4, 2009, pp. 1804-1815. doi:10.1109/TVT.2008.2005267
Y. Zeng and Y. Liang, “Covariance Based Signal Detections for Cognitive Radio,” Proceeding of 6th IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Ireland, 17-20 April 2007, pp. 202- 207.
A. Al-Dulaimi and L. Al-Saeed, “An Intelligent Scheme for First Run Cognitive Radios,” 4th International Conference on Next Generation Mobile Applications, Services and Technologies, Jordan, 27-29 April 2010.
J. H. Hauris, D. He, G. Michel and C. Ozbay, “Cognitive Radio and RF Communication Design Optimiasation Using Genetic Algorithm,” MILCOM, Florida, 29-31 October 2007.
G. Ganesan and Y. Li, “Agility Improvement through Cooperative Diversity in Cognitive Radio,” Proceedings of IEEE Global Telecommunications Conference (GLOBE-COM 2011), St. Louis, 28 November-2 December 2005, pp. 2505-2509.
G. Ganesan, “Cooperative Spectrum Sensing in Cognitive Radio Networks,” Proceedings of IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, Baltimore, 8-11 November 2005, pp. 137- 143.
D. Cabric, A. Tkachenko and R. Brodersen, “Spectrum Sensing Measurements of Pilot, Energy, and Collaborative Detection,” Proceedings of IEEE Military Communications Conference, Washington DC, 23-25 October 2006, pp. 1-7.
P. Venkateswaran, S. Shaw, S. Pattanayak and R. Nandi, “Cognitive Radio Ad-Hoc Networks: Some New Results on Multichannel Hidden Terminal Problem,” Communications and Network, Vol. 4 No. 4, 2012, pp. 342-348. doi:10.4236/cn.2012.44039
Q. Zhao and B. Sadler, “A Survey of Dynamic Spectrum Access,” IEEE Signal Processing Magazine, Vol. 24, No. 3, 2007, pp. 79-89. doi:10.1109/MSP.2007.361604
B. Wang and K. J. R. Liu, “Advances in Cognitive Radio Networks: A Survery,” IEEE Journal of Selected Topics in Signal Processing, Vol. 5, No. 1, 2011, pp. 5-23.
X. Dong, Y. Li, C. Wu and Y. Cai, “A Learner Based on Neural Network for Cognitive Radio,” 12th IEEE International Conference on Communication Technology (ICCT), Nanjing, 11-14 November 2010, pp. 893-896.
S. Dhanjal, “Artificial Neural Networks in Speech Processing: Problems and Challenges,” IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, Victoria, 26-28 August 2001, pp. 510-513.
P. Giribone, R. Revetria, M. Antonetti and R. Tabolacci, “Use of Artificial Neural Networks as Support for Energy Saving Procedures in Telecommunications,” Telecommunications Energy Conference (INTELEC), Phoenix, 10-14 September 2000, pp. 159-162.
Y. J. Tang, Q. Y. Zhang and W. Lin, “Artificial Neural Network Based Spectrum Sensing Method for Cognitive Radio,” 6th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), Chengdu, 23-25 September 2010, pp. 1-4.
S. Haykin, “Neural Networks: A Comprehensive Foundation,” Prentice-Hall, Upper Saddle River, 1999.
J. Sachs, I. Maric and A. Goldsmith, “Cognitive Cellular Systems within the TV Spectrum,” Proceedings of IEEE DySPAN, Stanford, 6 April 2010, pp. 1-12.
S. R. Martin, “Test of ATSC 8-VSB Reception Performance of Consumer Digital Television Receivers,” 2005 FCC/OET TR. 05-1017, Washington DC, 2 November 2005.
Bendov, “Transmitter SNR for Maximim Coverage,” IEEE Transaction on Broadcasting, Vol. 5, No. 4, 2008, pp. 784-785.
S. J. Shellhammer, A. K. Sadek and W. Zhang, “Tehcnical Challenges for Cognitive Radio in the TV White Space Spectrum”, Proceedings of Information Theory and Applications Workshop, California, 2009, pp. 323-333.