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 journalArticlepeer-review

6 Scopus citations


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.

Original languageBritish English
Article number9136806
Pages (from-to)1056-1068
Number of pages13
JournalIEEE Transactions on Cognitive Communications and Networking
Issue number3
StatePublished - Sep 2020


  • Achievable throughput
  • collaborative compressive sensing
  • energy consumption
  • energy efficiency
  • spectrum sensing


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