• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.564-571
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• 2009

In this paper, we propose out-of -band collaborative spectrum sensing scheme in the cognitive radio (CR) base station operated by the multiple frequency channels. Also this paper presents the signal detection results for ATSC digital TV signal as an incumbent signal and derives signal detection probability and false alarm probability for the out-of-band collaborative spectrum sensing scheme in frequency selective Rayleigh fading channel. Numerical results demonstrate that the sensing performance is improved by the out-of-band collaborative spectrum sensing in the case that the incumbent signal powers measured by the CR terminals of the multiple frequency channels are almost similar.

• ETRI Journal
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• v.41 no.2
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• pp.176-183
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• 2019

Spectrum sensing plays an important role in spectrum sharing. Energy detection is generally used because it does not require a priori knowledge of primary user (PU) signals; however, it is sensitive to noise uncertainty. An order statistics (OS) detector provides inherent protection against nonhomogeneous background signals. However, no analysis has been conducted yet to apply OS detection to spectrum sensing in a wireless channel to solve noise uncertainty. In this paper, we propose a robust spectrum sensing scheme based on generalized order statistics (GOS) and analyze the exact false alarm and detection probabilities under noise uncertainty. From the equation of the exact false alarm probability, the threshold value is calculated to maintain a constant false alarm rate. The detection probability is obtained from the calculated threshold under noise uncertainty. As a fusion rule for cooperative spectrum sensing, we adopt an OR rule, that is, a 1-out-of-N rule, and we call the proposed scheme GOS-OR. The analytical results show that the GOS-OR scheme can achieve optimum performance and maintain the desired false alarm rates if the coefficients of the GOS-OR detector can be correctly selected.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.9-17
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• 2020

When IoT sensor nodes are deployed in areas where data collection is challenging, sensors must be relocated if sensing holes occur due to improper placement of sensors or energy depletion, and data collection is impossible. The sensing hole's cluster header transmits a request message for sensor relocation to an adjacent cluster header through a specific relay node. However, since a specific relay node is frequently used, a member sensor located in a specific cluster area adjacent to the sensing hole can continuously receive the movement message. In this paper, we propose a method that avoids the situation in which the sensing hole cluster header monopolizes a specific relay node and allows the cluster header to use multiple relay nodes fairly. Unlike the existing method in which the relay node immediately responds to the request of the header, the method proposed in this paper solves a ping-pong problem and a problem that the request message is concentrated on a specific relay node by applying a method of responding to the request of the header using a timer. OMNeT++ simulator was used to analyze the performance of the proposed method.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.75-81
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• 2023

The significance of gas sensors has been emphasized in various industries and applications, owing to the growing significance of environmental, social, and governance (ESG) management in corporate operations. In particular, the monitoring of hazardous gas leakages and detection of fugitive emissions have recently garnered significant attention across several industrial sectors. As industrial workplaces evolve to ensure the safety of their working environments and reduce greenhouse gas emissions, the demand for high-performance gas sensors in industrial sectors dealing with toxic substances is on the rise. However, conventional gas-sensing systems have limitations in monitoring fugitive gas leakages at both critical and subcritical concentrations in complex environments. To overcome these difficulties, recent studies in the field of gas sensors have employed techniques such as mobile robotic olfaction, remote optical sensing, chemical grid sensing, and remote acoustic sensing. This review highlights the significant progress made in various technologies that have enabled accurate and real-time mapping of gas distribution and localization of hazardous gas sources. These recent advancements in gas-sensing technology have shed light on the future role of gas-detection systems in industrial safety.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.340-351
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• 2023

Wearable sensors designed for strain, pressure, and temperature measurements are essential for monitoring human movements, health status, physiological data, and responses to external stimuli. Notably, recent research has led to the development of high-performance wearable sensors using innovative materials and device structures that exhibit ultra-high sensitivity compared with their commercial counterparts. However, the quest for accurate sensing has identified a critical challenge. Specifically, the mechanical flexibility of the substrates in wearable sensors can introduce interference signals, particularly when subjected to varying external stimuli and environmental conditions, potentially resulting in signal crosstalk and compromised data fidelity. Consequently, the pursuit of non-interference sensing technology is pivotal for enabling independent measurements of concurrent input signals related to strain, pressure, and temperature, ensuring precise signal acquisition. In this comprehensive review, we present an overview of the recent advances in noninterference sensing strategies. We explore various fabrication methods for sensing strain, pressure, and temperature, emphasizing the use of hybrid composite materials with distinct mechanical properties. This review contributes to the understanding of critical developments in wearable sensor technology that are vital for their ongoing application and evolution in numerous fields.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.409-416
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• 2017

In this paper, we consider a framework of compressed sensing over finite fields. One measurement sample is obtained by an inner product of a row of a sensing matrix and a sparse signal vector. A recovery algorithm proposed in this study for sparse signals based probabilistic decoding is used to find a solution of compressed sensing. Until now compressed sensing theory has dealt with real-valued or complex-valued systems, but for the processing of the original real or complex signals, the loss of the information occurs from the discretization. The motivation of this work can be found in efforts to solve inverse problems for discrete signals. The framework proposed in this paper uses a parity-check matrix of low-density parity-check (LDPC) codes developed in coding theory as a sensing matrix. We develop a stochastic algorithm to reconstruct sparse signals over finite field. Unlike LDPC decoding, which is published in existing coding theory, we design an iterative algorithm using probability distribution of sparse signals. Through the proposed recovery algorithm, we achieve better reconstruction performance as the size of finite fields increases. Since the sensing matrix of compressed sensing shows good performance even in the low density matrix such as the parity-check matrix, it is expected to be actively used in applications considering discrete signals.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1546-1553
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• 2015

In cognitive radio technology, the overall capacity of communications systems can be improved without allocating additional bands by allowing secondary system to utilize the band when a primary system who has right to use the band does not utilize it. Therefore, spectrum sensing to determine the existence of primary system is utmost important in the cognitive radio technology. In this work, we consider a novel cooperative spectrum sensing in cognitive cellular systems. Especially, we consider the case in which heterogeneous primary systems coexist, i.e., heterogenous transmission power and sensing requirement of primary system, such that only portion of users in cognitive cellular systems are able to detect the primary system. In this case, we propose new cooperative spectrum sensing with multiple sensing stages to properly detect the existence of primary systems in this kind of situations. Moreover, we analyze the performance of conventional cooperative spectrum sensing schemes such as OR-rule, AND-rule and MAJORITY-rule under the existence of heterogeneous primary systems. Finally, we investigate the performance of the proposed scheme through computer based simulations and show that the existence of primary systems can be determined accurately by using our proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6A
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• pp.484-493
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• 2009

For the flexible frequency utilization, cognitive radio technique has been prominently considered. The most important requirement in cognitive radio networks is to protect the communications of primary users. Spectrum sensing task by secondary users should be seriously considered in cognitive radio networks, since the spectrum sensing process makes their current quality of service worse. In this paper, we propose the channel sensing scheduling method that keeps the requirements for protecting the primary and guarantee the secondary user's quality of service as possible. The quality of service of secondary user is analyzed in terms of packet delay and loss while the protection-requirements in terms of sensing interval and sensing time predefined. In numerical analysis, we can get appropriate parameters which guarantee QoS in various environment. And simulation results show that this method can improve the performance, delay and the number of transmitted packets against consecutive sensing method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.113-119
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• 2010

Wireless ad hoc network composed of low power devices has been operated in ISM bands. However, with the growing proliferation of wireless services, these bands are increasingly getting congested. In order to relieve the spectrum scarcity and inefficient spectrum utilization, ad ho cognitive radio was proposed. In this paper we propose the efficient spectrum sensing method to reduce power consumption and detect white space in ad hoc cognitive radio system. The wireless channel between a licensed user and CR systems is modeled as Gaussian channel, the distance between a licensed user and CR systems is assumed differently. Also, the wireless channel among CR systems is assumed as the perfect channel and the distance among CR systems is assumed close distance. CR systems sense the spectrum of the licensed user by using a energy detection method. From the simulation results, spectrum sensing performance of combining sensing result of CR systems with high received energy shows higher than combining sensing result of all CR systems and we can refer to the proposed sensing method in order to perform effective spectrum sensing with low power consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1208-1222
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• 2014

Due to the low utilization and scarcity of frequency spectrum in current spectrum allocation methodology, cognitive radio networks (CRNs) have been proposed as a promising method to solve the problem, of which spectrum sensing is an important technology to utilize the precious spectrum resources. In order to protect the primary user from being interfered, most of the related works focus only on the restriction of the missed detection probability, which may causes over-protection of the primary user. Thus the interference probability is defined and the interference-aware sensing model is introduced in this paper. The interference-aware sensing model takes the spatial conditions into consideration, and can further improve the network performance with good spectrum reuse opportunity. Meanwhile, as so many fading factors affect the spectrum channel, errors are inevitably exist in the reporting channel in cooperative sensing, which is improper to be ignored. Motivated by the above, in this paper, we study the throughput tradeoff for interference-aware cognitive radio networks over imperfect reporting channel. For the cooperative spectrum sensing, the K-out-of-N fusion rule is used. By jointly optimizing the sensing time and the parameter K value, the maximum throughput can be achieved. Theoretical analysis is given to prove the feasibility of the optimization and computer simulations also shows that the maximum throughput can be achieved when the sensing time and the parameter of K value are both optimized.