Performance Analysis of Compressed Sensing in Cognitive Radio Networks using l1-Minimization and Differential Evolution Algorithms

Namburu, Swetha; Duggineni, Chaitanya

doi:10.2139/ssrn.3351594

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Application Of Compressive Sensing To Wide-band Cognitive Ra...1

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2023

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“…Key to DSA is the cognitive radio (CR) that can sense the environment and adjust its transmitting parameters accordingly to not cause interference to other primary users of the frequency. Thus, spectrum sensing is a critical function of CR [30,31].…”

Section: Application Of Compressive Sensing To Wide-band Cognitive Ra...mentioning

confidence: 99%

Application of Compressive Sensing (CS) to Wide-Band Cognitive Radio signals

Nagah¹,

Mostafa²,

Megahed³

et al. 2023

IUSRJ

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Compressive Sensing (CS) is a digital signal processing developed theory that encloses the signal sampling and compression, based on the sparsity characteristics of signal. This can decrease sampling rate, so reduce computational complexity of the system without degrading the performance of the system. This paper describes the theoretical frame and a few key technical, then illustrates the application of compressed sensing theory to wide-band cognitive radio signals. Spectrum sensing is a critical issue in wide-band Cognitive Radio (CR) networks as it faces hard challenges such as high hardware cost, complexity, sampling rate and processing speed. Thus, this paper shows that Compressive Sensing could be exploited in wide-band Cognitive Radio networks to solve the spectrum sensing problems mentioned above.

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Section: Application Of Compressive Sensing To Wide-band Cognitive Ra...mentioning

confidence: 99%