• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1116-1132
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• 2010

In this paper, a new forward error correction (FEC) protocol is proposed for point-to-multipoint satellite links. Link-layer error control protocols in point-to-multipoint satellite links impose several problems such as unreliability and receiver-heterogeneity. To resolve the problem of heterogeneous error rates at different receivers, the proposed scheme exploits multiple multicast channels to which each receiver tunes. The more channels a receiver tunes to, the more powerful error correcting capability it achieves. Based on its own channel condition, each receiver tunes to as many channels as it needs, which prevents from receiving unwanted parities. Furthermore, each receiver saves the decoding time, processing overhead, and processing energy. Performance evaluation shows that the proposed scheme guarantees the target PER while saving energy. The proposed technique is highly adaptive to the channel variation with respect to the throughput efficiency, and provides scalable PER and throughput efficiency.

• Journal of Satellite, Information and Communications
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• v.11 no.1
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• pp.21-25
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• 2016

In this paper, we propose an algorithm for optimal selection of communications for smart lighting in heterogeneous networks. The smart lighting can be used for information communications and lighting simultaneously. To improve BER performance of smart lighting in heterogeneous networks, it adaptively selects a communication method among OCC, Wi-Fi, BLE based on distance between sensors and smart lightings, low power consumption for user requirements, operating time of smart lighting in Line-of-Sight(LOS)/Non-LOS channels. Thus, simulation results demonstrate effectiveness of the proposed algorithm contrary to baseline methods in LOS/NLOS channels.

• Environmental Engineering Research
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• v.25 no.4
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• pp.515-521
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• 2020

Nowadays, due to various pollution sources, it is essential for environmental scientists to monitor water quality. Phytoplanktons form the end of the food chain in water bodies and are one of the most important biological indicators in water pollution studies. Chlorophyll-A, a green pigment, is found in all phytoplankton. Chlorophyll-A concentration indicates phytoplankton biomass directly. Therefore, Chlorophyll-A is an indirect indicator of pollutants, including phosphorus and nitrogen, and their refinement and control are important. The present study, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were used to estimate the chlorophyll-A concentration in southern coastal waters in the Caspian Sea. For this purpose, Multi-layer perceptron neural networks (NNs) were applied which contained three and four feed-forward layers. The best three-layer NN has 15 neurons in its hidden layer and the best four-layer one has 5 in each. The three- and four- layer networks both resulted in similar root mean square errors (RMSE), 0.1($\frac{{\mu}g}{l}$), however, the four-layer NNs proved superior in terms of R² and also required less training data. Accordingly, a four-layer feed-forward NN with 5 neurons in each hidden layer, is the best network structure for estimating Chlorophyll-A concentration in the southern coastal waters of the Caspian Sea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.670-683
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• 2016

Network coding, as a new technique to improve the throughput, is studied combined with multi-relay model in this paper to address the challenges of long distance and power limit in deep space communication. First, an amplify-and-forward relaying approach based on analog network coding (AFNC) is proposed in multi-relay network to improve the capacity for deep space communication system, where multiple relays are introduced to overcome the long distance link loss. The design of amplification coefficients is mathematically formulated as the optimization problem of maximizing SNR under sum-power constraint over relays. Then for a dual-hop relay network with a single source, the optimal amplification coefficients are derived when the multiple relays introduce non-coherent noise. Through theoretic analysis and simulation, it is shown that our approach can achieve the maximum transmission rate and perform better over single link transmission for deep space communication.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.84-90
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• 2011

Handling paging mechanism at the IP layer (i.e., IP paging) makes it possible to support heterogeneous wireless access technologies, providing energy-saving and reduced location registration signaling overhead over IP-based mobile networks. However, IP paging may rather cause adverse effects under active communication environments because of significant paging signaling overhead and frequent paging delay. Therefore, in order to solve these problems, a cost-effective IP paging scheme is proposed in this paper, which enables a mobile node to perform selective registration and paging based on its profile information. Numerical results indicate that the proposed scheme has apparent potential to mitigate considerable paging signaling overhead and frequent paging delay in IP-based hierarchical mobile networks.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.1-12
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• 2020

Low-Orbit satellite mobile networks can provide services through miniaturized terminals with low transmission power, which can be used as reliable means of communication in the national public disaster network and defense sector. However, the high traffic environment in the emergency preparedness situation increases the new call blocking probability and the handover failure probability of the satellite network, and the increase of the handover failure probability affects the QoS because low orbit satellites move in orbit at a very high speed. Among the channel allocation methods of satellite communication, the FCA shows relatively better performance in a high traffic environment than DCA and is suitable for emergency preparedness situations, but in order to optimize QoS when traffic increases, the new call blocking and the handover failure must be minimized. In this paper, we propose LEO-DBC (LEO satellite dynamic beam width control) technique, which improves QoS by adaptive adjustment of beam width of low-orbit satellites and call time of terminals by improving FCA-QH method. Through the LEO-DBC technique, it is expected that the QoS of the mobile satellite communication network can be optimally maintained in high traffic environments in emergency preparedness situations.

• ETRI Journal
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• v.25 no.4
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• pp.211-218
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• 2003

This paper presents a dynamic resource allocation algorithm with multi-frequency time-division multiple access for the return link of interactive satellite multimedia networks such as digital video broadcasting return channel via satellite systems. The proposed timeslot assignment algorithm, called the very efficient dynamic timeslot assignment (VEDTA) algorithm, gives an optimal assignment plan within a very short period. The optimality and computational efficiency of this algorithm demonstrate that it will be useful in field applications.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.394-397
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• 2003

This paper has been studied a interworking signalling protocol between two hybrid networks by analyzing Satellite B-ISDN architecture, DSS2 Layer 3 Signalling protocol, B-ISUP protocol, S-BISUP protocol stack and so on. Also in the paper, messages and primitives have been defined for B-ISDN's Connection Type, Ownership and each protocol in order to connect point-to-multipoint. And then this paper has designed basic call procedures for OBP Satellite B-ISDN NNI interworking protocol, verified and implemented them.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.6
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• pp.756-759
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• 2012

This paper presents the multibeam service coverage of GEO(Geostationary Orbit) satellite and the practical antenna scheme scenarios to provide the universal communication services on the Korean peninsula. The proposed antenna systems consist of the simplest scheme and feed network so that they can be mounted on satellites. The feed networks are effectively organized according to the frequency and polarization plan. Despite simple structure, all scenarios meet the electrical performance by the optimization of feed allocation and feed excitation.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.33-41
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• 2003

Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.