• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.22-27
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• 2014

In this paper, we analyzed performance of FFT based on pilot sensing scheme for DTV signal in fading environments. In order to detect the present and absent for advanced television system committee digital television (ATSC DTV), a pilot detection scheme based on FFT is employed. Also, these signals are applied to each fading environment. For evaluating the spectrum sensing performance, detection probability is derived. When threshold is decided, we refer to constant false alarm rate (CFAR) scheme. From simulation results, it is confirmed that the spectrum sensing performance is improved as increase of the false alarm rate. The result of this paper can be applied to implement the spectrum sensing part of cognitive radio (CR) systems.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.60-67
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• 2007

The spectrum sensing is important for decision of using frequency band. It checks the frequency band for cognitive radio system. In this paper, we apply autocorrelation function to the energy detection method. We use the autocorrelation function to improve the performance of spectrum sensing method based on the energy detection method. This method is different from cyclostationary process method where parameters such as the mean or the autocorrelation function are time-varying periodically. And we propose improved method that is robust in poor radio environment. If the proposed method applies for sensing in the cognitive radio system, it will have the structural simplicity and the fast computation of spectrum sensing.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.8-13
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• 2012

In this paper, we investigate cooperative spectrum sensing scheme for sensor network-aided cognitive radio systems with energy harvesting capability. In the proposed model, each sensor node harvests ambient energy from environment such as solar, wind, mechanical vibration, or thermoelectric effect. We propose adaptive cooperative spectrum sensing scheme in which each sensor node adaptively carries out energy detection depending on the residual energy in its energy storage and then conveys the sensing result to the fusion center. From simulation results, we show that the proposed scheme minimizes the false alarm probability for given target detection probability by adjusting the number of samples for energy detector.

• ETRI Journal
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• v.42 no.6
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• pp.976-986
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• 2020

Internet of Things (IoT) is considered the future network to support wireless communications. To realize an IoT network, sufficient spectrum should be allocated for the rapidly increasing IoT devices. Through cognitive radio, unlicensed IoT devices exploit cooperative spectrum sensing (CSS) to opportunistically access a licensed spectrum without causing harmful interference to licensed primary users (PUs), thereby effectively improving the spectrum utilization. However, an open access cognitive IoT allows abnormal IoT devices to undermine the CSS process. Herein, we first establish a hard-combining attack model according to the malicious behavior of falsifying sensing data. Subsequently, we propose a weighted sequential hypothesis test (WSHT) to increase the PU detection accuracy and decrease the sampling number, which comprises the data transmission status-trust evaluation mechanism, sensing data availability, and sequential hypothesis test. Finally, simulation results show that when various attacks are encountered, the requirements of the WSHT are less than those of the conventional WSHT for a better detection performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.124-131
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• 2009

Cognitive radio has been proposed to mitigate the spectrum scarcity problem by allowing the secondary users to access the under-utilized frequency bands and opportunistically transmit. Spectrum sensing, as a key technology in cognitive radio, is required to reliably detect the presence of primary users to avoid the harmful interference. However, it would be very hard to reliably detect the presence of primary users due to the channel fading, shadowing. In this paper, we proposed a distributed cooperative spectrum sensing scheme based on conventional DF (decode-and-forward) cooperative diversity protocol. We fist consider the cooperation between two secondary users to illustrate that cooperation among secondary users can obviously increase the detection performance. We then compare the performance of DF based scheme with another conventional AF (amplify-and-forward) protocol based scheme. And it is found that the proposed scheme based on DF has a better detection performance than the one based on AF. After that, we extend the number of cooperative secondary users, and demonstrate that increasing the cooperation number can significantly improve the detection performance.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.877-889
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• 2016

In this paper, we introduce the basic components of the Cognitive Radio Networks along with possible threats. Specifically, we investigate the SSDF (Spectrum Sensing Data Falsification) attack which is one of the easiest attack to carry out. Despite its simplicity, the SSDF attack needs careful attention in order to build a secure system that resists to it. The proposed scheme utilizes the Anomaly Detection technique to identify malicious users as well as their sensing reports. The simulation results shows that the proposed scheme can effectively detect erroneous sensing reports and thus result in correct detection of the active primary users.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.162-171
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• 2014

Spectrum sensing is a key technical challenge for cognitive radio (CR). It is well known that multicycle cyclostationarity (MC) detection is a powerful method for spectrum sensing. However, a conventional MC detector is difficult to implement because of its high computational complexity. This paper considers reducing computational complexity by simplifying the test statistic of a conventional MC detector. On the basis of this simplification process, an improved MC detector is proposed. Compared with the conventional detector, the proposed detector has low-computational complexity and high-accuracy sensing performance. Subsequently, the sensing performance is further investigated for the cases of Rayleigh, Nakagami-m, Rician, and Rayleigh fading and lognormal shadowing channels. Furthermore, square-law combining (SLC) is introduced to improve the detection capability in fading and shadowing environments. The corresponding closed-form expressions of average detection probability are derived for each case by the moment generation function (MGF) and contour integral approaches. Finally, illustrative and analytical results show the efficiency and reliability of the proposed detector and the improvement in sensing performance by SLC in multipath fading and lognormal shadowing environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.765-774
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• 2013

In this paper, we present a cooperative compressed spectrum sensing scheme for correlated signals in decentralized wideband cognitive radio networks. Compressed sensing is a signal processing technique that can recover signals which are sampled below the Nyquist rate with high probability, and can solve the necessity of high-speed analog-to-digital converter problem for wideband spectrum sensing. In compressed sensing, one of the main issues is to design recovery algorithms which accurately recover original signals from compressed signals. In this paper, in order to achieve high recovery performance, we consider the multiple measurement vector model which has a sequence of compressed signals, and propose a cooperative sparse Bayesian recovery algorithm which models the temporal correlation of the input signals.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.72-77
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• 2011

Spectrum sensing is a critical functionality of CR network; it allow secondary user to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to primary use. Recently, wideband service has been increase for processing abundance of data traffic. So CR network needs a realizable implementation design of spectrum sensing for wideband. To get high resolution performance of wideband sensing must precede algorithm processing for reliability signal detection. By the way, the performance of spectrum sensing can be degraded due to fading and shadowing. In order to overcome this problem, we propose system model of wideband sensing scheme on energy detected collaborative technique. we divide wideband into narrowbands and use narrowbands to detect signal excepting some narrowbands including bad channel through the CSI. And we simulate and analyze in terms of detection probability with various SNR.