• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.59-66
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• 1993

In this paper we propose an adaptive update rate tracking algorithm for a phased array radar, based on the interacting multiple model(IMM) algorithm. The purpose of the IMM algorithm hers is twofold: 1) to estimate and predict the target states, and 2) to estimate the level of the process noise. Using the estimate of the process noise level adapted to target dynamics, the update interval is determined to maintain a desired prediction accuracy so that the radar system load is minimized. The adaptive update rate tracking algorithm is implemented for a phased array radar and evaluated with Monte Carlo simulations on various trajectories. The evaluation results of the proposed algorithm and a standard Kalman filter without the adaptive update rate control are presented to compare.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.25-28
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• 1999

Consider connection-oriented wireless cellular net-works. To establish a circuit or virtual circuit in such a network, a paging message is broadcast over a region at which the destined mobile station is presumed to reside, (identified as a paging area). For an effective paging mechanism, it is desirable to provide the location information of mobile stations to the network. In this paper, we consider a mobile controlled location update scheme under which each mobile station periodically reports its current location information to the network by using an inherent timer (without measuring the power of signals transmitted from base stations). Based on the latest information about a mobile station's location, a paging area is selected to page the mobile station. Note that under this scheme, a mobile station may not yet have reported its location change while sojourning out of the current paging area. In such situation, the mobile station can not receive a paging message destined to it. Frequent location updates can reduce the paging failure rate incurred by mobile stations'sojourning out of the paging area. However, larger bandwidth is needed for location update as the location update rate is increased. On the other hand, as the size of the paging area is increased, the paging failure rate is decreased, while larger bandwidth is required for paging. Thus, we first present a model for mobility, paging and location update processes, and secondly investigate the effect of network parameters on the paging failure rate and the amount of bandwidth used for paging and location update. Finally, we formulate problems to find proper values for the location update rate and paging area size under the constraints on the bandwidth usage levels for location update and paging.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.53-56
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• 2003

In order to enhance the system capacity of multi rate IEEE 802.11 WLAN, we propose the transmission rate select method using the control frame in this paper. The transmission rate is selected dynamically based on the RSSI(Received Signal Strength Indicator) of received control frame. And we also propose the Enhanced NAV Update method for Fragmented MPDU burst transmission in multirate WLAN environment. This method can improve the system capacity by support the burst transmission of fragmented MPDU.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.17-24
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• 2016

In this paper, we propose a AH LSU(Advanced Hybrid QoS Routing Link State Update) Algorithm that improves the performance of Hybrid LSU(Hybrid QoS Link State State Update) Algorithm with statistical information of flow holding time in network. AH LSU algorithm has had both advantages of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. It has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and include MLMR(Meaningless LSU Message Removal) mechanism. MLMR mechanism can remove the meaningless LSU message generating repeatedly in short time. We have evaluated the performance of the MLMR mechanism, the proposed algorithm and the existing algorithms on MCI simulation network. We use the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.55-62
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• 2014

This paper has proposed Hybrid QoS Routing Link State Update(LSU) Algorithm that has had a both advantage of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. Hybrid LSU algorithm can adapt the threshold based network traffic information and has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and determine the transmission of the message according to update rate per a unit of time. We have evaluated the performance of the proposed algorithm and the existing algorithms on MCI simulation network using the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm that it can diminish to 10% of the LSU message count.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.75-81
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• 2012

This paper has proposed Message Count Control Mechanism based Link State Update(LSU) Algorithm that has not had a strong influence on the depreciation of QoS routing performance. Most existing LSU algorithms have the limit that cannot control the count of LSU message. Especially, adaptive algorithms have a bad performance when traffic are excessive and fickle. We classify as the importance of LSU message that have a influence on available bandwidth and determine the transmission of the message according to update rate per a unit of time. We have evaluated the performance of the proposed model and the existing algorithms on MCI simulation network using the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• ETRI Journal
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• v.28 no.6
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• pp.815-818
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• 2006

In the global Internet, a constraint-based routing algorithm performs the function of selecting a routing path while satisfying some given constraints rather than selecting the shortest path based on physical topology. It is necessary for constraint-based routing to disseminate and update link state information. The triggering policy of link state updates significantly affects the volume of update traffic and the quality of services (QoS). In this letter, we propose an adaptive triggering policy based on link-usage statistics in order to reduce the volume of link state update traffic without deterioration of QoS. Also, we evaluate the performance of the proposed policy via simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.420-427
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• 2010

This paper describes a localization method based on Monte Carlo Localization approach for a mobile robot. The method uses range data which are measured from ultrasound transmitting beacons whose locations are given a priori. The ultrasound receiver on-board a robot detects the range from the beacons. The method requires several beacons, theoretically over three. The method proposes a sensor model for the range sensing based on statistical analysis of the sensor output. The experiment uses commercialized beacons and detector which are used for trilateration localization. The performance of the proposed method is verified through real implementation. Especially, it is shown that the performance of the localization degrades as the sensor update rate decreases compared with the MCL algorithm update rate. Though the method requires exact location of the beacons, it doesn't require geometrical map information of the environment. Also, it is applicable to estimation of the location of both the beacons and robot simultaneously.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.301-308
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• 1997

The learning speed of the neural networks, the most important factor in applying to real problems, greatly depends on the learning rate of the networks, Three approaches-empirical, deterministic, and stochastic ones-have been proposed to date. We proposed a new learning-rate selection algorithm using an evolutionary programming search scheme. Even though the performance of our method showed better than those of the other methods, it was found that taking much time for selecting evolutionary learning rates made the performance of our method degrade. This was caused by using static intervals (called static windows) in order to update learning rates. Out algorithm with static windows updated the learning rates showed good performance or didn't update the learning rates even though previously updated learning rates shoved bad performance. This paper introduce a window control scheme to avoid such problems. With the window control scheme, our algorithm try to update the learning ra es only when the learning performance is continuously bad during a specified interval. If previously selected learning rates show good performance, new algorithm will not update the learning rates. This diminish the updating time of learning rates greatly. As a result, our algorithm with the window control scheme show better performance than that with static windows. In this paper, we will describe the previous and new algorithm and experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.271-279
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• 2014

As an alternative way to overcome the weakness of the global navigation satellite system (GNSS) in hostile situation, a gravity gradient referenced navigation (GGRN) has been developed. This paper analyzed the performance of GGRN with respect to the initial errors, DB resolution as well as update rates. On the basis of simulations, it was found that the performance of GGRN is getting worse when initial errors exist but the navigation results are rapidly converged. Also, GGRN generates better results when DB resolution is higher and update rates are shorter than 20 seconds. However, it is difficult to deduce the optimal parameters for the navigation because some trajectories show better performance in case low-resolution DB is applied or long update rate is supposed. Therefore, further analysis to derive specific update conditions to improve the performance has been performed. Those update conditions would not be generalized for all cases although maximum improvement rate is over 200% in certain case. In the future, some more developments and tests on the combination of various geophysical data and/or algorithms are necessary to construct more stable and reliable navigation system.