• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3194-3210
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• 2022

Wall obstruction is the main factor leading to the non-line of sight (NLoS) error of indoor localization based on received signal strength indicator (RSSI). Modeling and correcting the path loss of the signals through the wall will improve the accuracy of RSSI localization. Based on electromagnetic wave propagation theory, the reflection and transmission process of wireless signals propagation through the wall is analyzed. The path loss of signals through wall is deduced based on power loss and RSSI definition, and the theoretical model of path loss of signals through wall is proposed. In view of electromagnetic characteristic parameters of the theoretical model usually cannot be accurately obtained, the statistical model of NLoS error caused by the signals through the wall is presented based on the log-distance path loss model to solve the parameters. Combining the statistical model and theoretical model, a hybrid model of path loss of signals through wall is proposed. Based on the empirical values of electromagnetic characteristic parameters of the concrete wall, the effect of each electromagnetic characteristic parameters on path loss is analyzed, and the theoretical model of regional path loss of signals through the wall is established. The statistical model and hybrid model of regional path loss of signals through wall are established by RSSI observation experiments, respectively. The hybrid model can solve the problem of path loss when the material of wall is unknown. The results show that the hybrid model can better express the actual trend of the regional path loss and maintain the pass loss continuity of adjacent areas. The validity of the hybrid model is verified by inverse computation of the RSSI of the extended region, and the calculated RSSI is basically consistent with the measured RSSI. The hybrid model can be used to forecast regional path loss of signals through the wall.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.41-47
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• 2002

Path setup considering QoS is one of the main problems to solve in Internet traffic engineering. In network restoration that is one of the traffic engineering components, to establish a backup path or backup path for a working path to be protected is the main task. The backup path should have enough bandwidth to guarantee the working paths. Thus this work requires the QoS routing solution that is to set up a backup path as well as a working path at the same time provisioning enough bandwidth. In this paper, we propose an algorithm to setup a backup path that shares the bandwidth of other backup paths whose working path does not pass along the same link with the working path we are considering. In this way we can reduce much bandwidth consumption caused by setting up backup paths. We also analyze the disjoint path computation algorithms. Finally we show simulation results how the algorithm can reduce the bandwidth consumption and how it will affect blocking when we setup paths.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.434-442
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• 2012

Several gateway selection schemes have been proposed that select gateway nodes based on a single Quality of Service (QoS) path parameter, for instance path availability period, link capacity or end-to-end delay, etc. or on multiple non-QoS parameters, for instance the combination of gateway node speed, residual energy, and number of hops, for Mobile Ad hoc NETworks (MANETs). Each scheme just focuses on the ment of improve only a single network performance, i.e., network throughput, packet delivery ratio, end-to-end delay, or packet drop ratio. However, none of these schemes improves the overall network performance because they focus on a single QoS path parameter or on set of non-QoS parameters. To improve the overall network performance, it is necessary to select a gateway with stable path, a path with themaximum residual load capacity and the minimum latency. In this paper, we propose a gateway selection scheme that considers multiple QoS path parameters such as path availability period, available capacity and latency, to select a potential gateway node. We improve the path availability computation accuracy, we introduce a feedback system to updated path dynamics to the traffic source node and we propose an efficient method to propagate QoS parameters in our scheme. Computer simulations show that our gateway selection scheme improves throughput and packet delivery ratio with less per node energy consumption. It also improves the end-to-end delay compared to single QoS path parameter gateway selection schemes. In addition, we simulate the proposed scheme by considering weighting factors to gateway selection parameters and results show that the weighting factors improve the throughput and end-to-end delay compared to the conventional schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1197-1205
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• 2007

An adaptive K-best detection scheme is proposed for MIMO systems. The proposed scheme changes the number of survivor paths, K based on the degree of the reliability of Zero-Forcing (ZF) estimates at each K-best step. The critical drawback of the fixed K-best detection is that the correct path's metric may be temporarily larger than K minimum paths metrics due to imperfect interference cancellation by the incorrect ZF estimates. Based on the observation that there are insignificant differences among path metrics (ML distances) when the ZF estimates are incorrect, we use the ratio of the minimum ML distance to the second minimum as a reliability indicator for the ZF estimates. So, we adaptively select the value of K according to the ML distance ratio. It is shown that the proposed scheme achieves the significant improvement over the conventional fixed K-best scheme. The proposed scheme effectively achieves the performance of large K-best system while maintaining the overall average computation complexity much smaller than that of large K system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1195-1210
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• 2012

In this paper, we propose a new signaling protocol as an extension of Generalized Multi-Protocol Label Switching (GMPLS) based PCE protocol for control carrier ethernet. The proposed protocol is not only compatible with the GMPLS PCE standard protocol, but also provides the topology discovery and configuration. In order to verify interoperability, we implement the proposed protocol as well as the system integrating functions including commercial system for testbed. In addition, we have simulated topology discovery test for proposed protocol performance.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.3
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• pp.264-269
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• 2013

This paper is to investigate propagation path characteristics of GPS potential jamming signal. To do this, the spherical ground diffraction model is applied to the potential jamming scenario referred to the GPS jamming events occurred in recent years. The fundamental theory on the propagation path loss is discussed and a specific model is applied to several vehicles types which have own heights of antennas in order to compare their propagation path loss values at same 2-D location. The transmitting powers are appropriately given as the ordinary GPS jamming events. And then the received powers in dBW are obtained with given transmitting powers and the estimated total loss. The result of received jamming power at various locations due to the given scenario was distinct. For example, propagation loss values were estimated as -147 ~ -142dBW and -167 ~ -162dBW in $10^6W$ and $10^4W$, respectively. This computation result of the loss can be seriously considered with the tolerable jammer power against L1- C/A GPS receiver under any real jamming situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3270-3294
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• 2020

Some things come easily to humans, one of them is the ability to navigate around. This capability of navigation suffers significantly in case of partial or complete blindness, restricting life activity. Advances in the technological landscape have given way to new solutions aiding navigation for the visually impaired. In this paper, we analyze the existing works and identify the challenges of path selection, context awareness, obstacle detection/identification and integration of visual and nonvisual information associated with real-time assisted mobility. In the process, we explore machine learning approaches for robotic path planning, multi constrained optimal path computation and sensor based wearable assistive devices for the visually impaired. It is observed that the solution to problem is complex and computationally intensive and significant effort is required towards the development of richer and comfortable paths for safe and smooth navigation of visually impaired people. We cannot overlook to explore more effective strategies of acquiring surrounding information towards autonomous mobility.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.10
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• pp.582-590
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits(CNC) is proposed. The analog circuits based optimal path planning is very useful since most of the optimal path planning problems require real time computation. There has already been a previous study to implement the dynamic programming with analog circuits. However, it could not be applied for the practically large size of problems since the algorithm employs the mechanism of reducing its input current/voltage by the amount of cost, which causes outputs of distant cells to become zero. In this study, a subgoal-based dynamic programming algorithm to compute the optimal path is proposed. In the algorithm, the optimal paths are computed regardless of the distance between the starting and the goal points. It finds subgoals starting from the starting point when the output of the starting cell is raised from its initial value. The subgoal is set as the next initial position to find the next subgoal until the final goal is reached. The global optimality of the proposed algorithm is discussed and two different kinds of simulations have been done for the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.187-191
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• 2012

This paper deals with a safe climbing path planning for unmanned automatic vehicles. Unlike the existing path planning schemes, the safety is the highest priority for our approach. To achieve this, the global potential field which includes a dangerous zone as well a given terrain information is generated, and the way-points are determined by using image processing such as the erosion operation. The proposed method can reduce the computation effort and the amount of information, and provide the safe climbing path which is similar to human's intuition.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.