Architecture of Cognitive Radio Networks

Abstract

Today’s wireless networks are characterized by fixed spectrum assignment policy. The spectral scarcity and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum, opportunistically. Cognitive Radio (CR) is that very paradigm for wireless communication, in which either a network or a wireless node reconfigures its transmission or reception parameters to communicate efficiently avoiding interference with licensed or unlicensed users. CR adapts itself to the newer environment on the basis of its intelligent sensing and captures the best available spectrum to meet user communication requirements. When the radio link features are extended to the network layer, the cognitive radios form the cognitive radio network. This book chapter is focused on cognitive radio network, architecture of the CR, and its relevance in the wireless and mobile Ad Hoc networks.

A new approach to predict COVID-19 using artificial neural networks

“…As a result of which no proper dataset is available to use as a reference. A synthetic multicriterion ( Banerjee, 2014 , Banerjee, 2015 , Banerjee, 2021 , Banerjee & Chakraborty, 2014 , Banerjee et al, 2017 , Banerjee et al, 2018b , Banerjee et al, 2018c , Banerjee et al, 2018a , Banerjee, Chakraborty, & Karmakar, 2013 , Banerjee & Karmakar, 2012 , Saha et al, 2019 , Saha et al, 2017 ) dataset has been coined by the authors to serve the purpose of this chapter, which is mentioned in the appendix ( Table A1 ). The attributes or symptoms and conditions that have been taken into consideration include age, body temperature, dry cough, chest pain, breathing rate, hypertension, cardiovascular diseases, diabetes, tiredness, current smoker, and contact with a person with fever or cold in the last few days.…”