Autocepstrum Approach for Spectrum Sensing in Cognitive Radio

Moawad, Azza; Yao, Koffi Clément; Mansour, Ali; Gautier, Roland

doi:10.1109/iswcs.2018.8491223

Cited by 4 publications

(7 citation statements)

References 12 publications

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“…• Detection of noise-like PU signals such as spread spectrum signals. For this purpose, we reviewed our proposed PB-ACD technique in [15] which detects the presence of a DS-SS signal by monitoring a major autocepstral peak. The improved PB-ACD technique is proposed for improving the detection process by providing a smoothing to the fluctuation so the ACEs.…”

Section: B Application Of Cepstral Analysis In Cognitive Radiomentioning

confidence: 99%

“…By taking the natural logarithm of S O (f ), we get the autocepstrum by: Fig. 18: The autocepstrum of the passband DS-SS signal; a large peak is located at a quefrency value that is equivalent to the reciprocal of the signal's operating frequency of 1 GHz [15] Since the BB-ACD utilizes the periodicity that may occur in the log-PSD of the received signal, we need to show at the beginning that the S Bs (f ) is periodic in the cepstral domain, and then consider the noisy periodicities in Z O (f ) due to the spectral fluctuations from S Es (f ). Consequently, this periodic feature can be utilized to formulate the detector test statistic.…”

Section: ) Improved Pb-acd Technique By Signal Smoothingmentioning

confidence: 99%

“…Indeed, the detection of low-power signals in CR is a spectrum sensing challenge, especially when the CR receiver has no knowledge of the specifications of the noise-like signal. The authors in [15] have evaluated the performance of the PB-ACD technique for detecting a DS-SS signal under the AWGN channel in the case of the SBSA. In this work, we aim to evaluate the performance of the smoothed PB-ACD in terms of the detection and the misdetection probabilities for two examples of noise-like signals, namely: a DS-SS signal and an Impulse Radio Ultra Wide Band (IR-UWB) signal.…”

Section: B Performance Evaluation Of the Proposed Pu Detection Technmentioning

confidence: 99%

“…As an alternative approach to the conventional energy detector, we propose two PU detection techniques that are based on evaluating the appropriate signal cepstrum for detecting noiselike signals for the case of the SBSA. It is worth mentioning that in [15] we proposed the PassBand AutoCepstrum Detector (PB-ACD) that analyzes the received signal in its passband version. Through the PB-ACD, the detection process merely depends on identifying a significant peak in the cepstral domain at the reciprocal of the center frequency of the target spectral band.…”

mentioning

confidence: 99%

“…Although the PB-ACD technique has shown its efficacy in detecting a Direct Sequence-Spread Spectrum (DS-SS) signal in [15], with an exact knowledge of the subbands center frequencies, its performance deteriorates when applied in the MBSA scenario due to the potential errors in estimating the subbands center frequencies. These errors may result in the misdetection and false-alarm problems.…”

mentioning

confidence: 99%

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A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

Moawad

Yao²,

Mansour

et al. 2020

IEEE Open J. Commun. Soc.

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Multiband spectrum access plays an essential role in cognitive radio systems so as to increase the network's throughput through wideband spectrum sensing. It includes identifying the number of subbands comprising a wide spectrum by edge detection, and also examining their occupancy through primary user detection techniques. Despite the offered accuracy of the wavelet-based approaches, their complexity becomes a drawback. Remarkably, the features revealing property of cepstral analysis and its implementation simplicity make it a suitable candidate for signal detection. Motivated by these reasons, this paper presents a wideband spectrum sensing approach based on cepstral analysis. First, we propose the differential log spectral density algorithm for the edge detection phase in order to detect the spectral boundaries within the wideband of interest. Also, we present a mathematical framework of the proposed algorithm and an expression for the detection threshold of the proposed detector is derived. The simulation results have showed a superior performance of the edge detection algorithm to different wavelet-based techniques at low-to-medium noise power. Used in conjunction with denoising, the proposed edge detector shows good detection results at low signal-to-noise ratio. For the primary user detection phase, we introduce the improved passband autocepstrum detector to tackle the misdetection problem of noise-like signals and it outperforms different state-of-the-art techniques. Finally, the uncertainty problem of the subbands center frequencies is addressed and the baseband autocepstrum detector is introduced as a potential solution to improve signal detection in frequency selective fading.

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Section: B Application Of Cepstral Analysis In Cognitive Radiomentioning

confidence: 99%

Section: ) Improved Pb-acd Technique By Signal Smoothingmentioning

confidence: 99%

Section: B Performance Evaluation Of the Proposed Pu Detection Technmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

Moawad

Yao²,

Mansour

et al. 2020

IEEE Open J. Commun. Soc.

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Spectrum Sensing by Cepstral Covariance Detection

et al. 2022

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Non-Cooperative Spectrum Sensing Strategy based on Recurrence Quantification Analysis in the Context of the Cognitive Radio

Kadjo¹,

Yao²,

Mansour³

et al. 2023

Preprint

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This paper addresses the problem of non-cooperative spectrum sensing in very low signal noise ratio (SNR) conditions. In our approach, detecting an unoccupied bandwidth consists to detect the presence or absence of a communication signal on this bandwidth. Major well known communication signals may contain hidden periodicities, we use the Recurrence Quantification Analysis (RQA) to reveal the hidden periodicities. RQA is very sensitive to a reliable estimation of the phase space dimension m or the time delay τ. In view of the limitations of algorithms proposed in the literature, we have proposed a new algorithm to estimate simultaneously the optimal values of m and τ. The new proposed optimal values allow the states reconstruction of the observed signal and then the estimation of the distance matrix. This distance matrix has particular properties which we have exploited to propose the Recurrence Analysis based Detector (RAD). RAD can detect a communication signal in a very low SNR condition. Using Receiver Operating Characteristic curves, our experimental results corroborate the robustness of our proposed algorithm comparing to classical widely used algorithms.

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Autocepstrum Approach for Spectrum Sensing in Cognitive Radio

Cited by 4 publications

References 12 publications

A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

Spectrum Sensing by Cepstral Covariance Detection

Non-Cooperative Spectrum Sensing Strategy based on Recurrence Quantification Analysis in the Context of the Cognitive Radio

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