• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.1
• /
• pp.361-378
• /
• 2012

Most of the current frequency hopping (FH) based dynamic spectrum access (DSA) methods concern a reactive channel access scheme with synchronous inter-channel spectrum sensing, i.e., FH is reactively triggered by the primary user (PU)'s return reported by spectrum sensing, and the PU channel to be switched to is assumed precisely just sensed or ready to be sensed, as if the inter-channel spectrum sensing moments are synchronous. However, the inter-channel spectrum sensing moments are more likely to be asynchronous, which risks PU suffering more interference. Moreover, the spectrum sensing is usually erroneous, which renders the problem more complex. To address this problem, we propose a proactive FH based DSA method against both erroneous spectrum sensing and asynchronous inter-channel spectrum sensing (moments). We term it as proactive DSA. The optimal FH sequence is obtained by dynamic programming. The complexity is also analyzed. Finally, the simulation results confirm the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.9
• /
• pp.4372-4389
• /
• 2019

Spectrum sensing has attracted much attention due to its significant contribution to idle spectrum detection in Cognitive Radio Networks. However, specialized discussion is on complexity-based sensing strategy for spectrum sensing seldom considered. Motivated by this, this paper is devoted to complexity-based sensing strategy for spectrum sensing. Firstly, three efficiency functions are defined to estimate sensing efficiency of a spectrum scheme. Then a novel sensing strategy is proposed given sensing performance and computational complexity. After that, the proposed sensing strategy is extended to energy detector, Cyclostationary feature detector, covariance matrix detector and cooperative spectrum detector. The proposed sensing strategy provides a novel insight into sensing performance estimation for its consideration of both sensing capacity and sensing complexity. Simulations analyze three efficiency functions and optimal sensing strategy of energy detector, Cyclostationary feature detector and covariance matrix detector.

• Journal of information and communication convergence engineering
• /
• v.9 no.2
• /
• pp.166-171
• /
• 2011

This paper investigates the design issues of spectrum sensing in the cognitive radio (CR) networks of opportunistic unlicensed spectrum access. The cognitive radios can perform a communication using the incumbent user spectrum band without the interference caused by the cognitive radio users. In this case, the cognitive radios must know the real-time radio environments of the incumbent user spectrum band using the spectrum sensing, beacon signal, and geo-location database access. Then in this paper, we are going to provide spectrum sensing issues which include the sensing techniques, the regulatory requirements, the analysis of DTV detection threshold, and main considerations associated with the spectrum sensing design in cognitive radio systems. Also, this paper introduces design trade-offs in order to optimize the sensing parameters such as sensing time and sensing complexity.

• Journal of information and communication convergence engineering
• /
• v.14 no.1
• /
• pp.1-8
• /
• 2016

Spectrum sensing in cognitive radio networks allows secondary users to sense the unused spectrum without causing interference to primary users. Cognitive radio requires more accurate sensing results from unused portions of the spectrum. Accurate spectrum sensing techniques can reduce the probability of false alarms and misdetection. In this paper, a two-stage spectrum sensing scheme is proposed for cooperative spectrum sensing in cognitive radio networks. In the first stage, spectrum sensing is executed for each secondary user using energy detection based on double adaptive thresholds to determine the spectrum condition. If the energy value lies between two thresholds, a fuzzy logic scheme is applied to determine the channel conditions more accurately. In the second stage, a fusion center combines the results of each secondary user and uses a fuzzy logic scheme for combining all decisions. The simulation results show that the proposed scheme provides increased sensing accuracy by about 20% in some cases.

• Journal of information and communication convergence engineering
• /
• v.13 no.4
• /
• pp.221-227
• /
• 2015

Spectrum sensing plays an essential role in a cognitive radio network, which enables opportunistic access to an underutilized licensed spectrum. In conventional cooperative spectrum sensing (CSS), all cognitive users (CUs) in the network spend the same amount of time on spectrum sensing and waste time in remaining silent when other CUs report their sensing results to the fusion center. This problem is solved by the superposition cooperative spectrum sensing (SPCSS) scheme, where the sensing time of a CU is extended to the reporting time of the other CUs. Subsequently, SPCSS assigns the CUs different sensing times and thus affects both the sensing performance and the throughput of the system. In this paper, we propose an algorithm to determine the optimal sensing time of each CU for SPCSS that maximizes the achieved system throughput. The simulation results prove that the proposed scheme can significantly improve the throughput of the cognitive radio network compared with the conventional CSS.

• Broadcasting and Media Magazine
• /
• v.11 no.1
• /
• pp.68-77
• /
• 2006

The Cognitive Radio (CR) technology is a promising solution for exploiting the limited spectrum resources and providing flexibility of spectrum usage. Future interactive broadcasting service can be realized by utilizing CR concept, since the up-link return channel can be found by the spectrum sensing method, which is core functional block of the CR system. In this paper, the spectrum sensing technologies of CR system is presented. First the system architecture of the CR with spectrum sensing block is presented. The suggested spectrum sensing technique consists of the coarse and the fine spectrum sensing. The coarse spectrum sensing technique adopted the wavelet transform to provide the multi-resolution sensing feature - Multi-Resolution Spectrum Sensing (MRSS). The fine spectrum sensing technique uses the beneficial properties of the autocorrelation function Analog Auto-Correlation (AAC). The simulation results for the proposed sensing technologies are presented for various incumbent signals.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.2
• /
• pp.321-323
• /
• 2012

Cognitive radio has been recently proposed to dynamically access unused-spectrum. Since the spectrum availability for opportunistic access is determined by spectrum sensing, sensing is identified as one of the most crucial issues of cognitive radio networks. The PHY-layer sensing, as a part of spectrum sensing in cognitive radio, concerns the sensing mechanism to determine channel to be sensed and to access. One of the important issues in the PHY-layer sensing control is to find an available sensing period and trade-off between spectrum sensing and data transmission. In this paper, we show the relationship between spectrum sensing and data transmission according to the sensing period. We analyze and propose the new scheme to evaluate optimal sensing period.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.1
• /
• pp.20-33
• /
• 2015

Spectrum sensing is a key component of cognitive radio. The prediction of the primary user status in a low signal-to-noise ratio is an important factor in spectrum sensing. However, because of noise uncertainty, secondary users have difficulty distinguishing between the primary signal and an unauthorized signal when an unauthorized user exists in a cognitive radio network. To resolve the sensitivity to the noise uncertainty problem, we propose an entropy-based spectrum sensing scheme to detect the primary signal accurately in the presence of an unauthorized signal. The proposed spectrum sensing uses the conditional entropy between the primary signal and the unauthorized signal. The ability to detect the primary signal is thus robust against noise uncertainty, which leads to superior sensing performance in a low signal-to-noise ratio. Simulation results show that the proposed spectrum sensing scheme outperforms the conventional entropy-based spectrum sensing schemes in terms of the primary user detection probability.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.48 no.3
• /
• pp.50-59
• /
• 2011

In this paper, we present a spectrum sensing method by exploiting the relationship of previous and current detected data sets in frequency domain. Most of the traditional spectrum sensing methods only consider the current detected data sets of Primary User (PU). Previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. By considering the relationship of the previous and current spectrum sensing, cross entropy-based spectrum sensing is proposed to detect PU signal more effectively, which has a strengthened performance and is robust. When previous detected signal is noise, the discriminating ability of cross entropy-based spectrum sensing is no better than conventional entropy-based spectrum sensing. To address this problem, we propose an improved cross entropy-based frequency-domain spectrum sensing. Regarding the spectrum sensing scheme, we have derived that the proposed method is superior to the cross entropy-based spectrum sensing. We proceed a comparison of the proposed method with the up-to-date entropy-based spectrum sensing in frequency-domain. The simulation results demonstrate the performance improvement of the proposed spectrum sensing method.

• Journal of Satellite, Information and Communications
• /
• v.9 no.4
• /
• pp.20-25
• /
• 2014

In this paper, we provide efficient spectrum sensing technology for smooth use of frequency and energy charge of multi-copter. The proposed structures focus on improving performance of spectrum sensing that is based on Ad-hoc network. First, we explain basic principles and disadvantages of cooperative spectrum sensing and ad-hoc based spectrum sensing. To solve these problems, in this paper, we employ the beamforming technology that guarantees higher transmit primary users' signal power to secondary users in ad-hoc network. The performance of proposed algorithm is analyzed in terms of detection probabilities, and the results of this paper can be applied to the various ad-hoc based Cognitive Radio system.