Spectrum sensing methods for detection of DVB-T signals in AWGN and fading channels

Danev, Danyo; Axell, Erik; Larsson, Erik G.

doi:10.1109/pimrc.2010.5671804

Cited by 28 publications

(12 citation statements)

References 9 publications

(20 reference statements)

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“…It is very important to note that the probability of false detection for the SP-CAF is very small compared to the DVB-T signals detectors presented in [28]. From the above-listed experimental results, it can be concluded that the performance of the SP-CAF detector is efficient for real signals, confirmed by its high detection probability and low probability of false alarm.…”

Section: Scenariomentioning

confidence: 81%

Blind spectrum sensing using symmetry property of cyclic autocorrelation function: from theory to practice

Safatly

Aziz

Nafkha

et al. 2014

J Wireless Com Network

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Spectrum sensing has been identified as the key step of the cognition cycle and the most important function for the establishment of cognitive radio. In this paper, a blind cyclostationary feature detector, which is based on the symmetry property of cyclic autocorrelation function (SP-CAF), is implemented and tested using universal software radio peripheral platform and GNU Radio open-source software development toolkit. Performance of the SP-CAF is compared to the classical energy detector via various tests conducted in real scenarios where both detection algorithms are employed to blindly sense the spectrum for opportunistic access. This study shows that the blind cyclostationary feature detector outperforms the classical energy detector while guaranteeing acceptable complexity and low sensing time. Moreover, different experimental results indicate that the blind sensing detector can achieve high detection probability at a low false alarm probability under real channel conditions and low signal-to-noise ratio.

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Section: Scenariomentioning

confidence: 81%

Blind spectrum sensing using symmetry property of cyclic autocorrelation function: from theory to practice

Safatly

Aziz

Nafkha

et al. 2014

J Wireless Com Network

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show abstract

“…This method is simple to implement. The works reported in [10] and [11] are examples of ED implementation for spectrum sensing. Due to its low complexity, energy detection is the most preferable and popular method.…”

Section: Related Workmentioning

confidence: 99%

A HOS-Based Blind Spectrum Sensing in Noise Uncertainty

Subekti¹,

Sugihartono²,

Syambas³

et al. 2015

J. ICT. Res. Appl.

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Abstract. Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the primary signal at a low signal to noise ratio (SNR). At a low SNR, the variance of noise fluctuates due to noise uncertainty. Detection of the primary signal will be difficult especially for blind spectrum sensing methods that rely on the variance of noise for their threshold setting, such as energy detection. Instead of using the energy difference, we propose a spectrum sensing method based on the distribution difference. When the channel is occupied, the distribution of the received signal, which propagates under a wireless fading channel, will have a non-Gaussian distribution. This will be different from the Gaussian noise when the channel is vacant. Kurtosis, a higher order statistic (HOS) of the 4 th order, is used as normality test for the test statistic. We measured the detection rate of the proposed method by performing a simulation of the detection process. Our proposed method's performance proved superior in detecting a real digital TV signal in noise uncertainty.

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“…It is considered that PU signal is a deterministic signal, this as sumption is valid for instance in the different standards defined in IEEE 802.22 working groups for Wireless Regional Area Networks (WRAN). As a practical example TV bands digital signals in Advanced Television Systems Committee (ATSC) standards which is used in North America, have predefined features such as the length of PN sequence and pilot symbol and synchronization patterns and thus makes our assumption valid and practical [7]- [10]. In the optimal spectrum sensing, the noise variance at each of the antennas, channel gains and PU signal are known.…”

Section: Basic Assumptions and Op Timal Detectormentioning

confidence: 99%

The effect of additional statistical side information on multiple antenna spectrum sensing

Tabesh

Taherpour

Khattab

2012

2012 IEEE Global Communications Conference (GLOBECOM)

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In this paper, we consider the problem of multiple antenna spectrum sensing in Cognitive Radios (CR) when some or all parameters are unknown. The Generalized Likelihood Ratio (GLR) test is the convectional method to solve the com posite hypothesis testing problem in which the detection and estimation sub-problems are considered separately. In this paper, the multiple spectrum sensing problem is solved using a novel approach in which the the detection and estimation sub-problems considered jointly and the resulted detectors are optimal under finite number of samples. We assume some additional side statistical information is available for unknown parameters and as theoretical results of the novel GLR detector imply , the optimal way of using this additional side information , is to use them in the Maximum A-Posteriori (MAP) or Minimum Mean Square Error (MMSE) estimation of unknown parameters for constructing the GLR tests. The simulation results show that the newly derived GLR detectors outperform traditional GLR detectors significantly. Also for the situation that all parameters are unknown the proposed detectors are compared with the Energy Detector (ED), where the simulation results indicate that the proposed detectors not only have significantly betterperformance, but also are robust to practical noise mismatch.

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Spectrum sensing methods for detection of DVB-T signals in AWGN and fading channels

Cited by 28 publications

References 9 publications

Blind spectrum sensing using symmetry property of cyclic autocorrelation function: from theory to practice

Blind spectrum sensing using symmetry property of cyclic autocorrelation function: from theory to practice

A HOS-Based Blind Spectrum Sensing in Noise Uncertainty

The effect of additional statistical side information on multiple antenna spectrum sensing

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