Paper Info
Title
On the Leverage of Superimposed Training for Energy-Efficient Spectrum Sensing in Cognitive Radio
Abstract
The efficient utilization of the radio-electric spectrum (or simply spectrum) is essential to satisfy the ever- increasing amount of bandwidth required by future wireless communications networks. Cognitive radio (CR) networks aim to improve this efficiency by dynamically exploiting the underutilized spectrum (also called spectrum opportunities). To identify these transmission opportunities, cognitive users might draw on spectrum sensing, although this task increases the energy consumption. For battery-powered terminals, this increment might represent a challenge, also considering that spectrum sensing must be recurrently performed. For a scenario in which the CR user first senses the spectrum and then, if allowed, transmit data, the average energy consumption depends on the time used for spectrum sensing and for data transmission, which also impacts the spectrum-efficiency. Thus, improving the energy-efficiency might implicate a reduction on the spectrum-efficiency. This paper analyses the energy-efficiency in the context of spectrum sensing of superimposed training-based transmissions, showing the advantages of using an enhanced spectrum sensing method in terms of the relationship between the spectrum and energy- efficiency.
Year
DOI
Venue
2020
10.1109/CCE50788.2020.9299115
2020 17th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)
Keywords
DocType
ISSN
spectrum sensing,energy-efficiency,cognitive radio,superimposed training
Conference
2642-3774
ISBN
Citations 
PageRank 
978-1-7281-8988-8
0
0.34
References 
Authors
8
5
Name
Order
Citations
PageRank
Lizeth Lopez-Lopez100.34
Marco Cardenas-Juarez2226.72
Enrique Stevens-Navarro300.34
Sami A. Aldalahmeh400.34
Marcos Katz553.23