On the leverage of superimposed training for energy-efficient spectrum sensing in cognitive radio |
|
Author: | Lopez-Lopez, Lizeth1; Cardenas-Juarez, Marco2; Stevens-Navarro, Enrique2; |
Organizations: |
1Faculty of Sciences Autonomous University of San Luis Potosi (UASLP) San Luis Potosi, Mexico 2Faculty of Sciences UASLP San Luis Potosi, Mexico 3Faculty of Engineering and Technology Al-Zaytoonah University of Jordan Amman, Jordan
4Centre for Wireless Communications, University Of Oulu, Oulu, Finland
|
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.8 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe202102175106 |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers,
2020
|
Publish Date: | 2021-02-17 |
Description: |
AbstractThe 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. see all
|
Series: |
International conference on electrical engineering, computing science, and automatic control |
ISSN: | 2642-3774 |
ISSN-E: | 2642-3766 |
ISSN-L: | 2642-3774 |
ISBN: | 978-1-7281-8987-1 |
ISBN Print: | 978-1-7281-8988-8 |
Pages: | 1 - 6 |
Article number: | 9299115 |
DOI: | 10.1109/CCE50788.2020.9299115 |
OADOI: | https://oadoi.org/10.1109/CCE50788.2020.9299115 |
Host publication: |
2020 17th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE) |
Conference: |
International Conference on Electrical Engineering, Computing Science and Automatic Control |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
213 Electronic, automation and communications engineering, electronics |
Subjects: | |
Funding: |
This work has been partially supported by the Mexican National Council for Science and Technology (CONACYT). |
Copyright information: |
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |