Energy Efficiency Analysis of Collaborative Compressive Sensing Scheme in Cognitive Radio Networks

Rajalekshmi Kishore, Sanjeev Gurugopinath, Sami Muhaidat, Paschalis C. Sofotasios, Mehrdad Dianati, Naofal Al-Dhahir

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
6 Downloads (Pure)

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 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.

Original languageEnglish
Pages (from-to) 1056-1068
Number of pages13
JournalIEEE Transactions on Cognitive Communications and Networking
Volume6
Issue number3
DOIs
Publication statusPublished - 2020
Publication typeA1 Journal article-refereed

Keywords

  • Achievable throughput
  • Cognitive radio
  • Collaboration
  • collaborative compressive sensing
  • Compressed sensing
  • Energy consumption
  • energy consumption
  • energy efficiency
  • Optimization
  • Sensors
  • spectrum sensing.
  • Throughput

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Energy Efficiency Analysis of Collaborative Compressive Sensing Scheme in Cognitive Radio Networks'. Together they form a unique fingerprint.

Cite this