• 제목/요약/키워드: Sensing Network

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Optimal Sensing Time for Maximizing the Throughput of Cognitive Radio Using Superposition Cooperative Spectrum Sensing

  • Vu-Van, Hiep;Koo, Insoo
    • Journal of information and communication convergence engineering
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    • 제13권4호
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    • pp.221-227
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    • 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.

인지 통신 네트워크의 스펙트럼 감지 및 전력 수집 방안 (Method of Spectrum Sensing and Energy Harvesting in Cognitive Communication Network)

  • 김태욱;공형윤
    • 한국인터넷방송통신학회논문지
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    • 제15권2호
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    • pp.45-49
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    • 2015
  • 본 논문에서는 인지 통신의 스펙트럼 감지 기법에 에너지 하베스팅 기법을 적용하여 2차 송신단의 전력 소모 없이 스펙트럼을 감지할 수 있을 뿐만 아니라 전력을 저장할 수 있는 방안을 제안하였다. 감지 및 수집 알고리즘은 에너지 하베스팅 기법으로 수집되는 전력량을 임계값과 비교하여 1차 네트워크의 스펙트럼 사용 유무를 판단하며 2차 송신단이 메시지를 전송하려는 경우, 1차 네트워크가 사용 중이라면 주파수를 변경하여 스펙트럼의 사용 유무를 판단하게 된다. 또한 전송하려는 메시지를 가지지 않는 경우, 지속적으로 전력을 수집하게 된다. 따라서 에너지 하베스팅 기법을 스펙트럼 감지 기법에 적용할 경우, 2차 네트워크의 전력이 낭비되는 문제점을 제거하고 전력을 충전하게 되므로 인지 네트워크의 활용도 및 효율성을 증가시킬 수 있다.

에너지 하베스팅이 적용된 스펙트럼 감지 방안 (Spectrum Sensing Method of Cognitive Network applying Energy Harvesting)

  • 김태욱;공형윤
    • 한국인터넷방송통신학회논문지
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    • 제15권3호
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    • pp.73-76
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    • 2015
  • 본 논문에서는 인지 통신의 스펙트럼 감지 기법에 에너지 하베스팅 기법을 적용하여 2차 송신단의 전력 소모없이 스펙트럼을 감지할 수 있을 뿐만 아니라 전력을 저장할 수 있는 방안을 제안하였다. 에너지 하베스팅 방법을 통해 수집된 전력과 임계값을 비교하여 1차 네트워크의 스펙트럼 사용 유무를 판단한다. 2차 송신단이 메시지를 전송하려는 경우, 1차 네트워크가 사용 중이라면 주파수를 변경하여 스펙트럼의 사용 유무를 판단하게 된다. 또한 전송하려는 메시지를 가지지 않는 경우, 지속적으로 전력을 수집하게 된다. 따라서 2차 네트워크의 지속적인 스펙트럼 감지로 인한 전력 낭비를 제거할 수 있으므로 인지 기술의 활용도 및 효율성을 증가시킬 수 있다.

Cooperative Spectrum Sensing for Cognitive Radio Networks with Limited Reporting

  • So, Jaewoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권8호
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    • pp.2755-2773
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    • 2015
  • Cooperative spectrum sensing increases the detection performance in a cognitive radio network, based on the number of sensing nodes. However, as the number of sensing nodes increases, the reporting overhead linearly increases. This paper proposes two kinds of cooperative spectrum sensing with limited reporting in a centralized cognitive radio network, a soft combination with threshold-based reporting (SC-TR) and a soft combination with contention-based reporting (SC-CR). In the proposed SC-TR scheme, each sensing node reports its sensing result to the fusion center through its own reporting channel only if the observed energy value is higher than a decision threshold. In the proposed SC-CR scheme, sensing nodes compete to report their sensing results via shared reporting channels. The simulation results show that the proposed schemes significantly reduce the reporting overhead without sacrificing the detection performance too much.

Characterization and modeling of a self-sensing MR damper under harmonic loading

  • Chen, Z.H.;Ni, Y.Q.;Or, S.W.
    • Smart Structures and Systems
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    • 제15권4호
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    • pp.1103-1120
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    • 2015
  • A self-sensing magnetorheological (MR) damper with embedded piezoelectric force sensor has recently been devised to facilitate real-time close-looped control of structural vibration in a simple and reliable manner. The development and characterization of the self-sensing MR damper are presented based on experimental work, which demonstrates its reliable force sensing and controllable damping capabilities. With the use of experimental data acquired under harmonic loading, a nonparametric dynamic model is formulated to portray the nonlinear behaviors of the self-sensing MR damper based on NARX modeling and neural network techniques. The Bayesian regularization is adopted in the network training procedure to eschew overfitting problem and enhance generalization. Verification results indicate that the developed NARX network model accurately describes the forward dynamics of the self-sensing MR damper and has superior prediction performance and generalization capability over a Bouc-Wen parametric model.

Self-weighted Decentralized Cooperative Spectrum Sensing Based On Notification for Hidden Primary User Detection in SANET-CR Network

  • Huang, Yan;Hui, Bing;Su, Xin;Chang, KyungHi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권11호
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    • pp.2561-2576
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    • 2013
  • The ship ad-hoc network (SANET) extends the coverage of the high data-rate terrestrial communications to the ships with the reduced cost in maritime communications. Cognitive radio (CR) has the ability of sensing the radio environment and dynamically reconfiguring the operating parameters, which can make SANET utilize the spectrum efficiently. However, due to the dynamic topology nature and no central entity for data fusion in SANET, the interference brought into the primary network caused by the hidden primary user requires to be carefully managed by a sort of decentralized cooperative spectrum sensing schemes. In this paper, we propose a self-weighted decentralized cooperative spectrum sensing (SWDCSS) scheme to solve such a problem. The analytical and simulation results show that the proposed SWDCSS scheme is reliable to detect the primary user in SANET. As a result, secondary network can efficiently utilize the spectrum band of primary network with little interference to primary network. Referring the complementary receiver operating characteristic (ROC) curves, we observe that with a given false alarm probability, our proposed algorithm reduces the missing probability by 27% than the traditional embedded spectrally agile radio protocol for evacuation (ESCAPE) algorithm in the best condition.

Compressed Sensing-Based Multi-Layer Data Communication in Smart Grid Systems

  • Islam, Md. Tahidul;Koo, Insoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권9호
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    • pp.2213-2231
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    • 2013
  • Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.

Energy Efficient Sequential Sensing in Multi-User Cognitive Ad Hoc Networks: A Consideration of an ADC Device

  • Gan, Xiaoying;Xu, Miao;Li, He
    • Journal of Communications and Networks
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    • 제14권2호
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    • pp.188-194
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    • 2012
  • Cognitive networks (CNs) are capable of enabling dynamic spectrum allocation, and thus constitute a promising technology for future wireless communication. Whereas, the implementation of CN will lead to the requirement of an increased energy-arrival rate, which is a significant parameter in energy harvesting design of a cognitive user (CU) device. A well-designed spectrum-sensing scheme will lower the energy-arrival rate that is required and enable CNs to self-sustain, which will also help alleviate global warming. In this paper, spectrum sensing in a multi-user cognitive ad hoc network with a wide-band spectrum is considered. Based on the prospective spectrum sensing, we classify CN operation into two modes: Distributed and centralized. In a distributed network, each CU conducts spectrum sensing for its own data transmission, while in a centralized network, there is only one cognitive cluster header which performs spectrum sensing and broadcasts its sensing results to other CUs. Thus, a wide-band spectrum that is divided into multiple sub-channels can be sensed simultaneously in a distributed manner or sequentially in a centralized manner. We consider the energy consumption for spectrum sensing only of an analog-to-digital convertor (ADC). By formulating energy consumption for spectrum sensing in terms of the sub-channel sampling rate and whole-band sensing time, the sampling rate and whole-band sensing time that are optimal for minimizing the total energy consumption within sensing reliability constraints are obtained. A power dissipation model of an ADC, which plays an important role in formulating the energy efficiency problem, is presented. Using AD9051 as an ADC example, our numerical results show that the optimal sensing parameters will achieve a reduction in the energy-arrival rate of up to 97.7% and 50% in a distributed and a centralized network, respectively, when comparing the optimal and worst-case energy consumption for given system settings.

Spectrum Sensing for Cognitive Radio Networks Based on Blind Source Separation

  • Ivrigh, Siavash Sadeghi;Sadough, Seyed Mohammad-Sajad
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권4호
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    • pp.613-631
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    • 2013
  • Cognitive radio (CR) is proposed as a key solution to improve spectral efficiency and overcome the spectrum scarcity. Spectrum sensing is an important task in each CR system with the aim of identifying the spectrum holes and using them for secondary user's (SU) communications. Several conventional methods for spectrum sensing have been proposed such as energy detection, matched filter detection, etc. However, the main limitation of these classical methods is that the CR network is not able to communicate with its own base station during the spectrum sensing period and thus a fraction of the available primary frame cannot be exploited for data transmission. The other limitation in conventional methods is that the SU data frames should be synchronized with the primary network data frames. To overcome the above limitations, here, we propose a spectrum sensing technique based on blind source separation (BSS) that does not need time synchronization between the primary network and the CR. Moreover, by using the proposed technique, the SU can maintain its transmission with the base station even during spectrum sensing and thus higher rates are achieved by the CR network. Simulation results indicate that the proposed method outperforms the accuracy of conventional BSS-based spectrum sensing techniques.

신경회로망 알고리즘과 ATmega128칩을 활용한 자동차용 지능형 AQS 시스템 (Intelligent AQS System with Artificial Neural Network Algorithm and ATmega128 Chip in Automobile)

  • 정완영;이승철
    • 제어로봇시스템학회논문지
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    • 제12권6호
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    • pp.539-546
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    • 2006
  • The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. The sensor module which includes two independent sensing elements for responding to diesel and gasoline exhaust gases, and temperature sensor and humidity sensor was designed for intelligent AQS in automobile. With this sensor module, AVR microcontroller was designed with back propagation neural network to a powerful gas/vapor pattern recognition when the motor vehicles pass a pollution area. Momentum back propagation algorithm was used in this study instead of normal backpropagation to reduce the teaming time of neural network. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation in this study. One chip microcontroller, ATmega 128L(ATmega Ltd., USA) was used for the control and display. And our developed system can intelligently reduce the malfunction of AQS from the dampness of air or dense fog with the backpropagation neural network and the input sensor module with four sensing elements such as reducing gas sensing element, oxidizing gas sensing element, temperature sensing element and humidity sensing element.