Cooperative wideband spectrum sensing in cognitive radio based on sparse real‐valued fast Fourier transform
Abstract
The Cognitive Radio (CR) plays a key role in identifying free bandwidths in the Radio Frequency (RF) spectrum. High‐speed Analog‐to‐Digital Converters are normally applied for spectrum sensing of sideband signals providing several raw data for digital signal processors resulted in energy‐inefficient complex circuits and hardware resources in digital signal processing blocks. In some instances, the frequency spectrum is sparsely occupied by various users, i.e., only a few active frequency bands exist at the same time. This feature enables CR application to use sub‐Nyquist sampling approaches for designing a system representing significantly reduced cost and power consumption, as well as improved processing speed. The current paper introduced a novel Cooperative Real‐valued Sparse Spread Spectrum Sensing algorithm (CR4S) based on a sub‐Nyquist sampling approach by employing the sparsity of the frequency spectrum and the real‐valued properties of the RF signal to identify free bandwidth with minimum computational complexity. The CR4S algorithm aimed at improving CR spectrum sensing by utilizing techniques such as Real‐valued FFT, Sparse Fast Fourier Transform, and collaborative spectrum sensing. The proposed algorithm has been approved by simulation to above 95% detection performance. The performance enhancement in the CR4S algorithm is an emerging advance being fascinating for portable CR devices.
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Published In
© 2021 The Institution of Engineering and Technology.
Publisher
John Wiley & Sons, Inc.
United States
Publication History
Published: 01 May 2020
Author Tags
Author Tags
- cooperative wideband spectrum sensing
- cognitive radio
- radiofrequency spectrum
- high‐speed energy‐inefficient analogue‐to‐digital converters
- sideband signals
- digital signal processors
- energy‐inefficient complex circuits
- hardware resources
- digital signal processing blocks
- active frequency bands
- improved processing speed
- real‐valued sparse spread spectrum sensing algorithm
- subNyquist sampling approach
- real‐valued properties
- RF signal
- minimum computational complexity
- CR spectrum sensing
- sparse FFT
- collaborative spectrum sensing
- portable CR devices
- CR4S algorithm
- sparse real‐valued fast Fourier transform
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