Signal Analysis and Classification of Digital Communication Signals using Adaptive Smooth-Windowed Wigner-Ville Distribution

Tan, Jo Lynn; Sha’ameri, Ahmad Zuri

doi:10.1109/nctt.2008.4814284

Cited by 11 publications

(9 citation statements)

References 11 publications

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“…This paper shows that the signal analysis and classification using the SWWVB is an improvement to the previous 681 methods [2][3][4]7] in terms of classification accuracy in fading environment. The method is capable to c1assity digital communication signals such as ASK, FSK and M-ary FSK with SNR greater than 14 dB at the accuracy 2: 80% in a slow fading channel with Doppler spread of 0,1 Hz.…”

Section: Discussionmentioning

confidence: 94%

“…However, most methods focus on modulation classification [2][3][4]. Since these signals are time varying, time-frequency analysis is the appropriate method and some of the popular methods used are wavelets [2,3], spectrogram, Wigner-Ville distributions (7,8]. Multipath fading in wireless communications produces instances of low SNR conditions [9] in the received signal that reduces the accuracy in analysis and classification.…”

Section: Introductionmentioning

confidence: 99%

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Signal analysis and classification of digital communication signal using time-frequency analysis techniques in the multipath fading environment

Tan

Sha’ameri

Chee

2010

10th International Conference on Information Science, Signal Processing and Their Applications (ISSPA 2010)

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Analysis and classification of digital modulation signals is an important feature of spectrum management and intelligence gathering. Various methods focus on classification according to modulation type with low accuracy at low signal-to-noise ratio (SNR). The presence of fading makes it more diffi cult due to the instantaneous variation in the SNR. Thus, the adaptive smooth-windowed Wigner Ville bispectrum (SWWVB) is proposed that combines the advantage of time-frequency analysis and higher order statistics (HOS). The estimated signal parameters from digital modulation signal such as ASK, FSK and M-ary FSK are then used as inputs to a rule based classifier. Compared to the bilinear time-frequency distribution, the system based on the adaptive SWWVB are able to maintain consistent classification accuracy in similar fading condition.

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Section: Discussionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Signal analysis and classification of digital communication signal using time-frequency analysis techniques in the multipath fading environment

Tan

Sha’ameri

Chee

2010

10th International Conference on Information Science, Signal Processing and Their Applications (ISSPA 2010)

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“…The transmitted signal of interest is a digital modulation signal, x(t) which can be formed by complex exponential as given below [18]:…”

Section: Signal Reception Modelmentioning

confidence: 99%

“…The adaptive smooth-windowed Wigner-Ville distribution (SWWVD) is used [18] and it belongs to class of quadratic time frequency distribution [21]. The S WWVD can be expressed as �(t,f) = f G(t, r) t * Kz(t, r) ej2rr/ T dr (7) T The bilinear product and the kernel function are given respectively as Kz(t, r) = z(t + r/2)z*(tr/2) (8) G(t, r) = H(t)w(r) (9) The kernel and its parameters are determined adaptively according to the signal parameters and the details are described in [18].…”

Section: B Time Frequency Analysismentioning

confidence: 99%

Multi-receiver system for improved signal reception in spectrum monitoring

Markom

Adom

Tan

et al. 2013

2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems

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In the communications field, many methods have been introduced in order to improve the quality of signal reception. This is because various parameters can limit the quality of signal reception such as multipath fading and interference that results the signal with low signal-to-noise ratio (SNR) or no signal reception. This paper presents a multi receiver system to improve signal reception and classification accuracy in radio communication system. Three receivers were utilized and each consists of antenna system, radio frequency (RF) front-end and down-conversion, time-frequency analysis, parameter estimation and signal classification. Then, the signal classification results are combined to obtain the final decision which is implemented using triple modulo redundancy (TMR) majority voting algorithm.The system was tested using six modulation signals (ASKI, ASK2, ASK3, FSKI, FSK2 and FSK3) with 100 trials for SNR from 2dB to 20dB. The performance of single-receiver and multi-receiver system is compared in terms of classification accuracy. Results show that the multi-receiver system was able to achieve 80 percent accuracy at minimum SNR of 2dB and the accuracy increases as the SNR increased.Index Terms-Multi sensor data fusion, multi-receiver system, improved signal reception and signal monitoring.

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“…However, the existence of cross-terms make this technique difficult to interpret the true signal characteristics. In addition, in order to remove the cross-terms, all types of signals cannot use the same kernel setting [24]. As a result, it is necessary to identify the optimal and the best kernel parameter for employing the TFD.…”

Section: Introductionmentioning

confidence: 99%

An improved smooth-windowed Wigner-Ville distribution analysis for voltage variation signal

Manap

Abdullah

Nikolovski

et al. 2020

IJECE

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This paper outlines research conducted using bilinear time-frequency distribution (TFD), a smooth-windowed wigner-ville distribution (SWWVD) used to represent time-varying signals in time-frequency representation (TFR). Good time and frequency resolutions offer superiority in SWWVD to analyze voltage variation signals that consist of variations in magnitude. The separable kernel parameters are estimated from the signal in order to get an accurate TFR. The TFR for various kernel parameters is compared by a set of performance measures. The evaluation shows that different kernel settings are required for different signal parameters. Verification of the TFD that operated at optimal kernel parameters is then conducted. SWWVD exhibits a good performance of TFR which gives high peak-to-side lobe ratio (PSLR) and signal-to-cross-terms ratio (SCR) accompanied by low main-lobe width (MLW) and absolute percentage error (APE). This proved that the technique is appropriate for voltage variation signal analysis and it essential for development in an advanced embedded system.

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Signal Analysis and Classification of Digital Communication Signals using Adaptive Smooth-Windowed Wigner-Ville Distribution

Cited by 11 publications

References 11 publications

Signal analysis and classification of digital communication signal using time-frequency analysis techniques in the multipath fading environment

Signal analysis and classification of digital communication signal using time-frequency analysis techniques in the multipath fading environment

Multi-receiver system for improved signal reception in spectrum monitoring

An improved smooth-windowed Wigner-Ville distribution analysis for voltage variation signal

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