OFDM Recognition Based on Cyclostationary Analysis in an Open Spectrum Scenario

Bixio, Luca; Oliveri, Giacomo; Ottonello, Marina; Regazzoni, Carlo S.

doi:10.1109/vetecs.2009.5073718

Cited by 11 publications

(6 citation statements)

References 14 publications

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“…In fact, if the parameter N SCF does not correspond to the dimension of the DFT used by the OFDM transmitter or the sampling frequency does not correspond to a integer multiple of the one used by the transmitter, then the SCF does not exhibit periodic behavior and reliable spectrum sensing cannot be obtained [14]. For these reasons, in general, a properly designed SCF estimator has to be provided for each class of primary users' signals to be classified.…”

Section: B Proposed Architectures and Considered Processing Algorithmmentioning

confidence: 99%

A Comparison between Stand-Alone and Distributed Architectures for Spectrum Hole Detection

Bixio

Ottonello

Raffetto

et al. 2010

2010 IEEE Wireless Communication and Networking Conference

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Abstract-In this paper two different cognitive radio architectures, i.e. stand-alone and distributed, are proposed for spectrum sensing purposes. In particular, both architectures implement a fast and reliable algorithm based on cyclic features extraction which allows to identify spectrum holes. The performances of such systems are compared in detecting primary users' presence in a monitored area classifying the used transmission standards, IEEE 802.11a and IEEE 802.16e. The considered scenario is challenging since both standards use the OFDM transmission technique, are designed to have the same bandwidth and use the same frequency band. A set of numerical simulations have been carried out to compare the performances of the proposed systems in a heavy multipath scenario and their advantages and disadvantages are discussed.

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Section: B Proposed Architectures and Considered Processing Algorithmmentioning

confidence: 99%

A Comparison between Stand-Alone and Distributed Architectures for Spectrum Hole Detection

Bixio

Ottonello

Raffetto

et al. 2010

2010 IEEE Wireless Communication and Networking Conference

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“…This issue is represented by Dynamic Spectrum Access (DSA) techniques [1]. The DSA techniques are based on the dynamic allocation of the operating frequencies and bandwidths to occupy the empty spaces in spectrum.…”

Section: Introductionmentioning

confidence: 99%

An automatic modulation classification technique using high-order statistics for multipath fading channels

Shih

Chang

2011

2011 11th International Conference on ITS Telecommunications

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In the last few years, the Dynamic Spectrum Access (DSA) has been a flexible strategy for wireless spectrum management. In vehicular communications, OFDM is usually used. The detection of dynamically allocated signals is a problem for a receiver with DSA technique. The automatic modulation classifier can recognize and demodulate the dynamically allocated signals in the OFDM system. We design a layered modulation classifier based on high-order statistics to classify the unknown modulated signal. The aim of the classifier is to defeat the unknown channel effect. We show the classification algorithm of signal detection in multipath environments, and discuss the performance of simulation results.

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“…For example, OFDM signals exhibit periodicities embedded in equally spaced sinusoidal carriers, cyclic prefix and pilot patterns [2]. These periodicities are exploited to detect PU through the Cyclostationary Autocorrelation Function (CAF) [7] or the Spectral Correlation Function (SCF) [2], the Fourier transform of CAF.…”

Section: Introductionmentioning

confidence: 99%

“…In [2], the cyclic features that arise from the periodic insertion of pilot tones are considered for the detection and the classification of OFDM signals. The authors propose a…”

Section: Introductionmentioning

confidence: 99%

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OFDM Signal Type Recognition and Adaptability Effects in Cognitive Radio Networks

Vizziello

Akyildiz

Augusti

et al. 2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

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Abstract-The ability of adapting to the environment in the most efficient way is a crucial issue in Cognitive Radio (CR) networks. For this purpose, an accurate estimation of the characteristics and activity of the Primary Users (PUs) is required. A system that takes into account heterogeneous PUs with several features is developed. A new scheme is integrated in the system to exploit these motleys and to improve the adaptability in CR networks. Through the proposed PU signal type recognition, the PU signal is detected and classified. The features of each PU type: the allowed interference levels, the bandwidth and the idle time, are extracted and exploited for CR adaptability effects. For this, a new CR throughput/interference adapter is proposed. The CR throughput is efficiently increased depending on the specific characteristics of PU types. Simulation results show that the proposed PU type recognition detects, distinguishes and classifies PU signals in Additive White Gaussian Noise (AWGN). It is shown that CR throughput varies with PU features for the improvement of CR adaptability.

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OFDM Recognition Based on Cyclostationary Analysis in an Open Spectrum Scenario

Cited by 11 publications

References 14 publications

A Comparison between Stand-Alone and Distributed Architectures for Spectrum Hole Detection

A Comparison between Stand-Alone and Distributed Architectures for Spectrum Hole Detection

An automatic modulation classification technique using high-order statistics for multipath fading channels

OFDM Signal Type Recognition and Adaptability Effects in Cognitive Radio Networks

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