• 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.

• Journal of KIISE
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• v.43 no.12
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• pp.1412-1419
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• 2016

In cognitive radio sensor networks (CRSNs), secondary users (SUs) can occupy licensed bands opportunistically without causing interferences to primary users (PUs). SUs perform spectrum sensing to detect the presence of PUs. Sensing time is a critical parameter for spectrum sensing that can yield a tradeoff between sensing performance and secondary throughput. In this study, we investigate new approaches for spectrum sensing by exploring the tradeoff from a) spectrum sensing for PU detection (SSPD) and b) spectrum sensing for secondary throughput (SSST). In the proposed scheme, the first sensing result of the current frame determines the dynamic performance of the second spectrum sensing. Energy constraint in CRSNs leads to maximized network energy efficiency via optimization of sensing time. Simulation results show that the proposed scheme of SSPD and SSST improves network performance in terms of energy efficiency and secondary throughput, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4625-4641
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• 2016

The performances of two commonly used feature detectors for wireless energy-harvesting cognitive radio systems are compared with the energy detector under energy causality and collision constraints. The optimal sensing duration is obtained by analyzing the effect of the detection threshold on the average throughput and collision probability. Numerical examples show that the covariance detector has the optimal sensing duration depending on an appropriate choice of the detection threshold, but no optimal sensing duration exists for the ratio of average energy to minimum eigenvalue detector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.458-466
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• 2008

Spectrum sensing is the key challenge in implementing cognitive radio system, which enables unlicensed users to identify "white holes" in the spectrum allocated to primary users and utilize them efficiently. Recent studies have proposed three major sensing methods for WRAN systems, including matched filter, energy and feature detector. However, there are some drawbacks along with them. In this paper, we propose an enhanced energy detector that extends the ability of conventional one, which can differentiate the primary users from each other as well as the noise with different maximum-to-mean power ratio. Furthermore, a novel structure of cognitive radio detector employing the proposed algorithm is also analyzed to implement spectrum sensing. The simulation result shows that our proposed scheme performs well in the individual sensing environment and can satisfy the requirement with high detection probability.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.98-113
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• 2016

A reactor vessel level monitoring system measures the water level in a reactor during normal operation and abnormal conditions. A drop in the water level can expose nuclear fuel, which may lead to fuel meltdown and radiation spread in accident conditions. A level monitoring system mainly consists of a sensing line and pressure transmitter. Over a period of time boron sediments or other impurities can clog the line which may degrade the accuracy of the monitoring system. The aim of this study is to determine blockage in a sensing line using the energy of the composite signal. An equivalent Pi circuit model is used to simulate blockages in the sensing line and the system's response is examined under different blockage levels. Composite signals obtained from the model and plant's unblocked and blocked channels are decomposed into six levels of details and approximations using a wavelet filter bank. The percentage of energy is calculated at each level for approximations. It is observed that the percentage of energy reduces as the blockage level in the sensing line increases. The results of the model and operational data are well correlated. Thus, in our opinion variation in the energy levels of approximations can be used as an index to determine the presence and degree of blockage in a sensing line.

• Journal of KIISE
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• v.43 no.1
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• pp.119-125
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• 2016

Cognitive radio technology can allow secondary users (SUs) to access unused licensed spectrums in an opportunistic manner without interfering with primary users (PUs). Spectrum sensing is a key technology for cognitive radio (CR). However, few studies have examined energy-efficient spectrum sensing in cognitive radio sensor networks (CRSNs). In this paper, we propose an energy-efficient cooperative spectrum sensing nodes selection scheme for cluster-based cognitive radio sensor networks. In our proposed scheme, false alarm probability and energy consumption are considered to minimize the number of spectrum sensing nodes in a cluster. Simulation results show that by applying the proposed scheme, spectrum sensing efficiency is improved with a decreased number of spectrum sensing nodes. Furthermore, network energy efficiency is guaranteed and network lifetime is substantially prolonged.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.19-26
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• 2010

In this paper, we propose an efficient decision rule in order to get better chance to detect the unused spectrum assigned to a licensed user and improve reliability of spectrum sensing performance. Each secondary user receives the signals from the licensed user. And the resulting signals input to an energy detector. Then, each sensing result is combined and used to make a decision whether the primary user is present at the licensed spectrum band or not. In order to make the reliable decision, we apply an efficient decision rule that is called as a majority rule in this paper. The simulation results show that spectrum sensing performance with the proposed decision rule is more reasonable and efficient than that with conventional decision rules.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.292-294
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• 2003

Evapotranspiration estimations are essential for monitoring drought, wild land fire risk etc. In this study, a surface energy balance method, which combines meteorological observations with spectral data derived from remote sensing measurements, was used to estimate the regional evapotranspiration in the Mongolia, a large arid and semi-arid region with heterogeneous surface conditions. The Surface Energy Balance method has been applied to Landsat+ETM and NOAA-AVHRR sensors for the estimation of evapotranspiration in the grassland of Mongolia. As a result, a daily evapotranspiration map of Mongolia was produced.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.1-9
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• 2015

Recently, cognitive radio technology has been spotlighted for the efficient use of limited frequency technology. The most important part of CR is to protect the incumbent user's communications. Therefore, CR user should be sensing the currently using channel and another hopping channel for sudden appearance of the Incumbent User. In this paper, we propose the cooperative channel sensing to protect the IU considering each CR user's remained power and sensing-zone, sense the spectrum bands in a fairly distributed manner and share the results among the users within respective sensing zone. Sensing scheme including inband sensing and outband sensing is utilized. The inband sensing is in charge of current using channel scanning while the outband sensing mainly cares about other channels. The performance results by computer simulations show that our sensing scheduling scheme reduces the number of sensing nodes and saves energy need to channel sensing.

• ETRI Journal
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• v.44 no.3
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• pp.389-399
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• 2022

Wireless sensor networks (WSNs) are one of the basic building blocks of Internet of Things (IoT) systems. However, the wireless sensing nodes in WSNs suffer from energy constraint issues because the replacement/recharging of the batteries of the nodes tends to be difficult. Furthermore, a number of realistic IoT scenarios, such as habitat and battlefield monitoring, contain mobile sensing elements, which makes the energy issues more critical. This research paper focuses on realistic WSN scenarios that involve mobile sensing elements with the aim of mitigating the attendant energy constraint issues using the concept of radio-frequency (RF) energy extraction. The proposed technique incorporates a cluster head election workflow for WSNs that includes mobile sensing elements capable of RF energy harvesting. The extensive simulation analysis demonstrated the higher efficacy of the proposed technique compared with the existing techniques in terms of residual energy, number of functional nodes, and network lifetime, with approximately 50% of the nodes found to be functional at the 4000th, 5000th, and 6000th rounds for the proposed technique with initial energies of 0.25, 0.5 and 1 J, respectively.