Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Energy efficiency analysis of collaborative compressive sensing scheme in cognitive radio networks

Tools
- Tools
+ Tools

Kishore, Rajalekshmi, Gurugopinath, Sanjeev, Muhaidat, Sami, Sofotasios, Paschalis C., Dianati, Mehrdad and Al-Dhahir, Naofal (2020) Energy efficiency analysis of collaborative compressive sensing scheme in cognitive radio networks. IEEE Transactions on Cognitive Communications and Networking, 6 (3). pp. 1056-1068. doi:10.1109/TCCN.2020.3007901

[img]
Preview
PDF
WRAP-Energy-efficiency-analysis-collaborative-compressive-sensing-cognitive-radio-Dianati-2020.pdf - Accepted Version - Requires a PDF viewer.

Download (1318Kb) | Preview
Official URL: https://doi.org/10.1109/TCCN.2020.3007901

Request Changes to record.

Abstract

In this paper, we investigate the energy efficiency of conventional collaborative compressive sensing (CCCS) scheme, focusing on balancing the tradeoff between energy efficiency and detection accuracy in cognitive radio environment. In particular, we derive the achievable throughput, energy consumption and energy efficiency of the CCCS scheme, and then formulate an optimization problem to determine the optimal values of parameters which maximize the energy efficiency of the CCCS scheme. The maximization of energy efficiency is proposed as a multi-variable, non-convex optimization problem, and we provide approximations to reduce it to a convex optimization problem. We highlight that errors due to these approximations are negligible. Subsequently, we analytically characterize the tradeoff between dimensionality reduction and collaborative sensing performance of the CCCS scheme, i.e., the implicit tradeoff between energy saving and detection accuracy. It is shown that the resulting loss due to compression can be recovered through collaboration, which improves the overall energy efficiency of the system.

Item Type: Journal Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Compressed sensing (Telecommunication) -- Energy consumption, Cognitive radio networks
Journal or Publication Title: IEEE Transactions on Cognitive Communications and Networking
Publisher: IEEE
ISSN: 2372-2045
Official Date: September 2020
Dates:
DateEvent
September 2020Published
8 July 2020Available
Date of first compliant deposit: 21 October 2020
Volume: 6
Number: 3
Page Range: pp. 1056-1068
DOI: 10.1109/TCCN.2020.3007901
Status: Peer Reviewed
Publication Status: Published
Publisher Statement: © 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.
Access rights to Published version: Restricted or Subscription Access

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us