Adaptive double-threshold based energy detector for spectrum sensing in cognitive radio networks

Abstract

In cognitive radio networks, spectrum sensing is used to sense the unused spectrum in an opportunistic manner. In this paper, we propose an energy detector utilizing adaptive double threshold (ED_ADT) for spectrum sensing, which improves detection performance as well as overcomes sensing failure problem. The detection threshold is made adaptive to the fluctuation of the received signal power in each local detector of secondary user. Numerical results show that proposed ED_ADT scheme outperforms conventional energy detector by 12.8% at -8 dB signal-to-noise ratio (SNR) in terms of probability of detection alarm (P d ). While utilizing cooperative spectrum sensing (CSS) with ED_ADT scheme, it is further found that adaptive double threshold improves detection performance around 26.8% and 7.6% as compared to CSS with single threshold and hierarchical with quantization method at -10 dB SNR, respectively, under the case when a small number of sensing nodes are used in spectrum sensing.

Two-Stage Spectrum Sensing Scheme Using Fuzzy Logic for Cognitive Radio Networks

“…In contrast, because the performance degrades sharply as the noise uncertainty increases, a dynamic threshold algorithm was proposed to combat noise uncertainty [9]. In [10], the author solved the sensing failure problem at a local node using two-bit quantization. The scheme is used to divide the confused region into four equal quantization intervals with the same weight.…”

Novel Spectrum detector for IEEE 802.22 Wireless Regional Area Network

“…In [15], authors have shown the curve of PU signal and noise signal in which authors discussed that detection of PU signal from noise signal is easy if both signals do not overlap to each other. Suppose detector receives PU signal then it declares H 1 i.e.…”

“…But, if PU signal and noise both intersects to each other then it is very difficult to sense desired signals. The area between λ 1 and λ 2 , known as confused region [15]. λ 1 is called upper bound and λ 2 is lower bound.…”

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“…In [3], authors have done the performance analysis of transmission based spectrum sensing techniques in terms of probability of false alarm (P f ), probability of detection (P d ), and probability of miss-detection alarm (P m ) and concluded final results. Further, a new sensing scheme based on double thresholds scheme have proposed in [4], which provided better detection results. While, in [5] authors have shown the comparative study between [4] scheme and existing cyclostationary feature detection scheme, which concluded that [4] performed better performance than cyclostationary feature detection scheme.…”