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Big Spectrum Data and Deep Learning Techniques for Cognitive Wireless Networks

Big Spectrum Data and Deep Learning Techniques for Cognitive Wireless Networks
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Author(s): Punam Dutta Choudhury (Gauhati University, India), Ankumoni Bora (Gauhati University, India)and Kandarpa Kumar Sarma (Gauhati University, India)
Copyright: 2018
Pages: 28
Source title: Deep Learning Innovations and Their Convergence With Big Data
Source Author(s)/Editor(s): S. Karthik (SNS College of Technology, Anna University, India), Anand Paul (Kyungpook National University, South Korea)and N. Karthikeyan (Mizan-Tepi University, Ethiopia)
DOI: 10.4018/978-1-5225-3015-2.ch003

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Abstract

The present world is data driven. From social sciences to frontiers of research in science and engineering, one common factor is the continuous data generation. It has started to affect our daily lives. Big data concepts are found to have significant impact in modern wireless communication systems. The analytical tools of big data have been identified as full scale autonomous mode of operation which necessitates a strong role to be played by learning based systems. The chapter has focused on the synergy of big data and deep learning for generating better efficiency in evolving communication frameworks. The chapter has also included discussion on machine learning and cognitive technologies w.r.t. big data and mobile communication. Cyber Physical Systems being indispensable elements of M2M communication, Wireless Sensor Networks and its role in CPS, cognitive radio networking and spectrum sensing have also been discussed. It is expected that spectrum sensing, big data and deep learning will play vital roles in enhancing the capabilities of wireless communication systems.

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