Maximum - Minimum Energy Based Spectrum Sensing under Frequency Selectivity for Cognitive Radios

Abstract

Cognitive Radio (CR) technology which uses intelligent signal processing at the physical layer of a wireless system has been considered for coordinating better the spectral resources. In this study, we investigate spectrum sensing methods which utilize the frequency variability of the energy spectral density which is introduced by the primary transmissions. The variability is partly due to the transmitted spectrum shape and party introduced by the frequency selective multipath channel. The spectral variability is observed by dividing the sensing frequency band into relatively narrow subbands and comparing the subband energies. We compare the subband energy based methods against the eigenvalue based sensing method, which exploits the signal correlations introduced by the primary transmission. Eigenvalue based sensing is known to be robust against the inevitable noise uncertainty, which severely limits the usability of energy detection for primaries with low SNR. Our results demonstrate for the subband energy detection methods, similar robustness against noise uncertainty as the eigenvalue based methods have.

Autonomous Compressive-Sensing-Augmented Spectrum Sensing

“…These benefits enable the proposed scheme to be implementable for spectrum sharing, especially over the 3.5GHz spectrum and the higher frequencies. Moreover, we shall extend the proposed scheme with advanced detector such as frequency domain autocorrelation [22] and maximumminimum energy detection sensing algorithm [46] to further enhance the ability against the noise uncertainty and frequency selective channel in future work. APPENDIX PROOF OF THE THEOREM 1 Let X ∈ R n be an arbitrary fixed unit vector, i.e., ||X|| 2 2 = 1 for simplicity, and the linear projection X → Y is defined by T w o -s t e p C S -b a s e d s c h e m e o v e r 3 .…”

A review on energy based spectrum sensing in Cognitive Radio Networks

“…In [15], a novel sub band spectrum sensing (energy based) is introduced where the sub band energy based sensing methods are developed. These are conceptual and computational in nature.…”

Novel filter bank-based cooperative spectrum sensing under practical challenges for beyond 5G cognitive radios

“…Especially, spectrum sensing under low signal-to-noise ratio (SNR) is widely covered in the literature, under conditions where the noise dominates the weak PU signal [3,4]. Under these conditions, the spectrum sensing becomes critically sensitive to imperfect knowledge of the power and characteristics of noise and interferences [5][6][7].…”

“…Moreover, maximum-minimum energy detector (Max-Min ED) has been found to be a robust and effective non-cooperative spectrum sensing scheme [6,7]. This approach applies subband decomposition of the received signal and the difference of maximum and minimum subband energies as a test statistic.…”

“…This approach applies subband decomposition of the received signal and the difference of maximum and minimum subband energies as a test statistic. This method has been shown to provide acceptable performance at the low SNR regime with noise uncertainty (NU) [6,7]. The intuitive simplistic idea behind these approaches is that in certain scenarios, the minimum subband energy can be regarded as an estimate for the noise variance.…”