• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.8 no.3
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• pp.111-115
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• 2009

Cognitive Radio (CR) technology is proposed for using the unused spectrum band efficiently because of the spectrum scarcity problems. Spectrum sensing is one of the most challenging issues in cognitive radio system. In this paper, we focus on the signal detection of WiBro system band. As most of the modulated signals can be treated as cyclostationary random process, we can detect the signal of the OFDM signals in WiBro system. OFDM symbols using WiBro system have several pilot subcarriers and periodic pilots have cyclostationary characteristic. To improve the detection performance, we get diversity gain using multiple antennas.

• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.28-32
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• 2014

In this paper, we analyzed the performance of cyclostationary signal detection scheme for LTE system. We applied the cyclostationary signal detection scheme to the cognitive radio(CR) technology, which improves the usage efficiency of spectrums and shares frequencies, and we detected the signal in the long term evolution(LTE) band. LTE system has been designated as the standard to improve the maximum data rate and provide the low latency in the 3rd generation partnership project(3GPP). In this paper, we generated the LTE signals based on the orthogonal frequency division multiple access(OFDMA) and analyzed the performance of signal detection in accordance with the segment and threshold of the generated signals. Gaussian channel was used in the simulation and we discussed the future studies to apply the CR to the LTE system.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.379-383
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• 2008

Cognitive Radio (CR) technology is proposed for using the unused spectrum band efficiently because of the spectrum scarcity problems. Spectrum sensing is one of the most challenging issues in cognitive radio system. In this paper, we focus on the signal detection of WiBro system band. As most of the modulated signals can be treated as cyclostationary random process, we can detect the signal of the OFDM signals in WiBro system. OFDM symbols using WiBro system have several pilot subcarriers and periodic pilots have cyclostationary characteristic. To improve of the detection performance, we get diversity gain using multiple antennas.

• Journal of Communications and Networks
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• v.6 no.2
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• pp.93-105
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• 2004

This paper discusses cyclostationary interference suppression for multiuser wired communication systems. Crosstalk interference from digital signals in multipair cables has been shown to be cyclostationary. Many crosstalk equalization or suppression techniques have been proposed which make implicit use of the cyclostationarity of the crosstalk interferer. In this paper, the convergence and steady-state behaviors of a fractionally spaced equalizer (FSE) in the presence of multiple cyclostationary crosstalk interference are thoroughly analyzed by using the equalizer's eigenstructure. The eigenvalues with multiple cyclostationary interference depend upon the folded signal and interferer power spectra, the cross power spectrum between the signal and the interferer, and tile cross power spectrum between the interferers, which results in significantly different initial convergence and steady-state behaviors as compared to the stationary noise case. The performance of the equalizer varies depending on the relative clock phase of the symbol clocks used by the signal and multiple interferers. Measued characteristics as well as analytical model of NEXT/FEXT channel are used to compute the optimum and worst relative clock phases among the signal and multiple interferers.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.119-122
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• 2016

Feature detection is recognized as an accurate spectrum sensing approach when the information of the desired signal is partly known at the receiver. This type of detection was proposed to overcome large noise environment. Cyclostationary detection is an example of feature detection in spectrum sensing technique in cognitive radio. However, the cyclostationary process calculation requires a lot of processing time and information about the designed signals. On the other hand, energy detection spectrum sensing is widely known as a simple and compact spectrum sensing technique. However, energy detection is highly affected by large noise and lead to high detection error probability. In this paper, the combination of energy detection and cyclostationary is proposed in order to increase the accuracy and decrease the calculation and processing time. The two-layer threshold is utilized in order to reduce the complexity of computation and processing time in cyclostationary which can lead to the improved throughput of the system. The simulation result shows that the implementation of energy-based cyclostationary detector can help to improve the performance of the system while it can considerably reduce the required time for signal detection.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.245-251
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• 2013

This paper addresses the issue of time-difference-of-arrival (TDOA) estimation for complex noncircular signals. First, under the wide-sense stationary assumption, we derive the maximum likelihood (ML) estimator and the Cramer-Rao lower bound for Gaussian noncircular signals in Gaussian circular noise. The ML estimator uses the second-order statistics information of a noncircular signal more comprehensively when compared with the cross-correlation (CC) and the conjugate CC estimators. Further, we present a scheme to modify the traditional signal-selective TDOA methods for noncircular signals on the basis of the cyclostationarity of man-made signals. This scheme simultaneously exploits the information contained in both the cyclic cross-correlation (CCC) and the conjugate CCC of a noncircular signal.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.195-204
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• 2014

In this paper, we propose an automatic modulation classification method for ten digitally modulated baseband signals, such as 2-FSK, 4-FSK, 8-FSK, MSK, BPSK, QPSK, 8-PSK, 16-QAM, 32-QAM, and 64-QAM based on higher order statistics of cyclostationary process. The first order cyclic moments and higher order cyclic cumulants of the signal are used as features of the modulation signals. The proposed method consists of two stages. At the first stage, we classify modulation signals as M-FSK and non-FSK using peaks of the first order cyclic moment. At the next step, we apply the Gaussian mixture model-based classifier to classify non-FSK. Simulation results are demonstrated to evaluate the proposed scheme. The results show high probability of classification even in the presence of frequency and phase offsets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7C
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• pp.672-679
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• 2006

Cognitive radio, which is designed to dynamically adapt its transmission to the environments, is believed to be one of the fundamental techniques for future spectrum utilization. As the first step of cognitive radio, spectrum sensing is treated as the most important technique, through which cognition is well explained. In this paper, we propose a spectral correlation based detection method for spectrum sensing. An unlicensed secondary user system operating in TV broadcast bands is taken as an example. Based on the cyclostationarity of communication signals, spectral correlation function is used to minimize the effect of random noise and interference. Energy measurement and peak detection based criteria are proposed. Simulation results show that the proposed detection method outperforms the energy detection and is more suitable for spectrum sensing in cognitive radios.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.517-524
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• 2015

The fast and accurate spectrum sensing over an ultra-wide bandwidth is a big challenge for the radio environment cognition. Considering sparse signal feature, two novel compressed sensing schemes are proposed, which can reduce compressed sampling rate in contrast to the traditional scheme. One algorithm is dynamically adjusting compression ratio based on modulation recognition and identification of symbol rate, which can reduce compression ratio. Furthermore, without priori information of the modulation and symbol rate, another improved algorithm is proposed with the application potential in practice, which does not need to reconstruct the signals. The improved algorithm is divided into two stages, which are the approaching stage and the monitoring stage. The overall sampling rate can be dramatically reduced without the performance deterioration of the spectrum detection compared to the conventional static compressed sampling rate algorithm. Numerous results show that the proposed compressed sensing technique can reduce sampling rate by 35%, with an acceptable detection probability over 0.9.

• Journal of Satellite, Information and Communications
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• v.1 no.1
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• pp.5-11
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• 2006

Cognitive radio, which is designed to dynamically adapt its transmission to its environments is believed to be one of the fundamental techniques for the future spectrum utilization. As the first step of cognitive radio, spectrum sensing is treated as the most important technique. In this paper, we propose a spectral correlation based detection method for spectrum sensing. Based on the cyclostationarity of communication signals, spectral correlation function is used to minimize the effect of random noise and interference. The ROC performance of conventional energy detection is shown. Simulation result show that the proposed detection method outperforms the energy detection and more suitable for spectrum sensing in cognitive radios.