Abstract
Cognitive radio (CR) is the solution for the current spectral underutilized problems, Context awareness and environment awareness are the key functions of CR nowadays. A software radio with reconfiguration capacity will become Cognitive Radio by imparting intelligence to SDR using Artificial Intelligence Techniques. There are processes in CR such as spectrum sensing, monitoring, and management involves the use of AI techniques. Artificial Intelligence (AI) is directed along with “cognitive” functions for better learning and classification. Recently deep learning involves more “self-learning” algorithms without any supervision. Hence it is important to discuss the various AI techniques for better resource optimization in CR networks. Optimization parameters are different for different techniques depend upon the radio environment. The type of AI technique for a particular application is random.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Clancy, T.C.: Dynamic spectrum access in cognitive radio networks. http://128.8.127.3/~jkatz/THESES/clancy.pdf (2006)
Goldberg, D.E.: A book on Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Pub Co (1989)
Rabiner, L.R., Juang, B.-H.: A Book on Fundamentals of Speech Recognition (2004)
Amudha, V., Venkataramani, B., Vinoth Kumar, R., Ravishankar, S.: SOC Implementation of HMM Based Speaker Independent Isolated Digit Recognition System. https://doi.org/10.1109/vlsid.2007.144 (2007)
Amudha, V., Ramesh, G.P.: Dynamic Spectrum Allocation for Cognitive Radio Using Genetic Algorithm. https://pdfs.semanticscholar.org/6e28/dafb1d44e3cf870933993fe7846f3e9e93be.pdf (2013)
Matinmikko, M., Ser, J.D., Rauma, T., Mustonen, M.: Fuzzy-Logic Based Framework for Spectrum Availability Assessment in Cognitive Radio Systems. https://doi.org/10.1109/jsac.2013.131117 (2013)
Singh, S.K., Singh, G., Pathak, V., Roy, K.C.: Spectrum management for cognitive radio based on genetic algorithm. Int. J. Adv. Res. Comput. Sci. (2011). http://dx.doi.org/10.26483/ijarcs.v2i1.295
Mitola, J., Maguare, J.Q.: Cogn. Radio Mak. Softw. Radio More Pers. (1999). https://doi.org/10.1109/98.788210
Zhao, Z., Peng, Z., Zheng, S., Shang, J.: Cogn. Radio Spectr. Alloc. Evol. Algorithm (2009). https://doi.org/10.1109/TWC.2009.080939
Rieser, C.J., Rondeau, T., Bostian, C.W., Gallagher, T.: Cognitive Radio Testbed: Further Details and Testing of a Distributed Genetic Algorithm Based Cognitive Engine for Programmable. https://doi.org/10.1109/milcom.2004.1495152 (2004)
Meziane, F., Vadera, S.: Artificial Intelligence Applications for Improved Software Engineering Development: New Prospects. https://doi.org/10.4018/978-1-60566-758-4.ch014 (2010)
Tewari, J., Arya, S., Singh, P.N.: Approach of intelligent software agents in future development. Int. J. Adv. Res. Comput. Sci. Softw. Eng. http://ijarcsse.com/Before_August_2017/docs/papers/Volume_3/5_May2013/V3I4-0319.pdf (2013)
Ammar, H.H., Abdelmoez, W., Hamdi, M.S.: Software Engineering Using Artificial Intelligence Techniques: Current State and Open Problems. https://pdfs.semanticscholar.org/0010/5a98161f98000cefd1880f39fc005319ec33.pdf (2012)
Harman, M.: The role of artificial intelligence. Softw. Eng. (2011). https://doi.org/10.1109/RAISE.2012.6227961
Jain, P.: Interaction Between Software Engineering and Artificial Intelligence-A Review, www.enggjournals.com/ijcse/doc/IJCSE11-03-12-072.pdf (2011)
Nachamai, M., Vadivu, M.S., Tapaskar, V.: Enacted Software Development Process Based on Agent methodologies. https://pdfs.semanticscholar.org/2bc8/e776687cc749d0bd5b1bfbc2f28f22cc6a3a.pdf (2011)
Ganesh Babu, R., Amudha, V.: Spectrum Sensing Techniques in Cognitive Radio Networks: A Survey. https://doi.org/10.1016/j.procs.2016.05.158
Ganesh Babu, R., Amudha, V.: Analysis of Distributed Coordinated Spectrum Sensing in Cognitive Radio Networks. https://www.ripublication.com/ijaer_spl/ijaerv10n6spl_114.pdf (2015)
Ganesh Babu, R., Amudha, V.: Performance Analysis of Distributed Coordinated Spectrum Sensing in Cognitive Radio. Networks (2015). https://doi.org/10.5829/idosi.mejsr.2015.23.ssps.13
Ganesh Babu, R., Amudha, V.: Cluster Technique Based Channel Sensing in Cognitive Radio Networks. www.serialsjournals.com/serialjournalmanager/pdf/1463980714.pdf (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ganesh Babu, R., Amudha, V. (2019). A Survey on Artificial Intelligence Techniques in Cognitive Radio Networks. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-13-1951-8_10
Download citation
DOI: https://doi.org/10.1007/978-981-13-1951-8_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1950-1
Online ISBN: 978-981-13-1951-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)