• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1873-1880
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• 2016

Most of the energy used to operate a cellular network is consumed by a base station (BS), and reducing the transmission power of a BS is required for energy-efficient cellular networks. In this paper, a distributed transmit power control (TPC) algorithm is proposed based on the flocking model to improve the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm each mobile station (MS) in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking model and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases. Consequently, it significantly improves the energy efficiency of a cellular network.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.405-410
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• 2006

This paper presents the design of a USB home controller and a home control system that specially is focused on controlling home appliances as a part of home network systems, the implementation of the USB device access class in an OSGi service platform and a home security system as an application. Designed USB home controllers are able to control various home appliances. They can be used not only to control big home appliances like a boiler but also to control small home appliances like a toaster because they are low-cost solutions. The USB home controller supports real time control using the interrupt transfer of the USB specification. And It is easy to use by homemakers who have no technical knowledge of the system because they just plug and unplug it in a home server then it automatically joins and leaves a home control system. This technique is based on hot-plug and the USB Device Access class in an OSGi Service Platform. The USB Device Access class supports the coordination of automatic detection and attachment of the USB home controller on an OSGi Service Platform, and it downloads and installs device drivers on demand. For an application, we implemented and tested a home security system using two USB home controllers and a CDMA module.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of Advanced Navigation Technology
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• v.11 no.3
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• pp.306-312
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• 2007

Present TCP/IP networks have some service quality problems. They delay various kinds of traffic, while increased traffic bottle necks, a phenomena experienced by too many internet users. Therefore, as use of the network increases, building up a stable network service is needed. Thus, network managers desperately need the best, most effective traffic control and wide-band services. Until now there has been no other way of increasing wide-band use of lines, particularly because of the expenses a limit solutions of solving continuously to increasing traffic problems. This study suggests a problem solving method under the base of 802.16e(Wibro) which will be widely used in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1419-1436
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• 2020

For an energy harvesting sensor network, when the network lifetime is not the only primary goal, maximizing the network performance under environmental energy harvesting becomes a more critical issue. However, clustering protocols that aim at providing maximum information throughput have not been thoroughly explored in Energy Harvesting Wireless Sensor Networks (EH-WSNs). In this paper, clustering protocols are studied for maximizing the data transmission in the whole network. Based on a long short-term memory (LSTM) energy predictor and node energy consumption and supplement models, an uneven clustering protocol is proposed where the cluster head selection and cluster size control are thoroughly designed for this purpose. Simulations and results verify that the proposed scheme can outperform some classic schemes by having more data packets received by the cluster heads (CHs) and the base station (BS) under these energy constraints. The outcomes of this paper also provide some insights for choosing clustering routing protocols in EH-WSNs, by exploiting the factors such as uneven clustering size, number of clusters, multiple CHs, multihop routing strategy, and energy supplementing period.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.4
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• pp.92-99
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• 1997

This paper proposed a control method to improve the efficiency of monitoring method by applying the nural network for an alarm processing method(APM)in an elevator facility of apartment complex. This APM is based on the cumulative generalized delta rule of backpropagation in neural network.It was used to infer the minimum alarms among multi-fired alarms, and then the inferred alarm can be dis¬played maintenance information of facility by using a pre-defined troubleshoot knowledge base. For validating the proposed monitoring method of this thesis, simulation results are compared with the operation of existing monitoring system and the way of alarm processing. The simulation method used to the three case of virtual scenario. As comparison results, a proposed method in this paper could be proved the applied possibility of an neural network and the performance in fields of facilities maintenance.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.846-856
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• 2016

Wireless sensor networks (WSNs) are widely applied in monitoring and control of environment parameters. It is sometimes necessary to disseminate data through wireless links after they are deployed in order to adjust configuration parameters of sensors or distribute management commands and queries to sensors. Several approaches have been proposed recently for data dissemination in WSNs. However, none of these approaches achieves both high efficiency and low complexity simultaneously. To address this problem, cluster-tree based network architecture, which divides a WSN into hierarchies and clusters is proposed. Upon this architecture, data is delivered from base station to all sensors in clusters hierarchy by hierarchy. In each cluster, father broadcasts data to all his children with instantly decodable network coding (IDNC), and a novel scheme targeting to maximize total transmission gain (MTTG) is proposed. This scheme employs a new packet scheduling algorithm to select IDNC packets, which uses weight status feedback matrix (WSFM) directly. Analysis and simulation results indicate that the transmission efficiency approximate to the best existing approach maximum weight clique, but with much lower computational overhead. Hence, the energy efficiency achieves both in data transmission and processing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.95-97
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• 2010

Recently, CAN network technology and MOST network are introduced in vehicle to control many electronic devices and to provide entertainment service. Many interconnected devices operate in MOST network which has ring topology such as CD-ROM(DVD), AMP, VIDEO CAMERA, VIDEO DISPLAY, GPS NAVIGATION and so on. In this paper, The input image of CAMERA in the MOST network is used for determining the movement direction of vehicle. Even though the position information was received from GPS, it is difficult to directly determine the direction of moving vehicle in certain areas such as the parallel road structure. This paper designs and implements the method to determine vehicle's direction by real-time matching between CAMERA image and object image base on image DB.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.367-373
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• 2022

Femtocells have recently been recognized for their potential to boost network capacity, improve end-user QoS and throughput, and do so at a cheap cost and with ease of implementation. The use of femtocells in indoor environments, such as residential buildings with neighboring homes, is becoming more popular. Femtocells are subject to interference from other femtocells, and the unwanted effects of interference are amplified when femtocells are deployed in close proximity to one another. As a consequence, the network's overall performance is degraded to a significant degree. One of the strategies that is thought to be effective in reducing the impact of interference is altering the transmission power of the femtocells. In this paper, a dynamic downlink transmission power of femtocells is suggested. In accordance with the observed cost function unit, each femtocell automatically changes its transmission power. If a femtocell causes too much interference for its neighbors, its transmission power level will be limited by that interference's rate. A simulation experiment is conducted to validate the effectiveness of the suggested system when compared with other schemes. When compared to previous schemes, which are addressed in this study, the numerical results show that the proposed strategy could provide more capacity while also ideally mitigating the influence of interference among co-channel deployed femtocells.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.226-234
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• 2024

The frequent handover problem and playing ping-pong effects in 5G (5th Generation) ultra-dense networking cannot be effectively resolved by the conventional handover decision methods, which rely on the handover thresholds and measurement reports. For instance, millimetre-wave LANs, broadband remote association techniques, and 5G/6G organizations are instances of group of people yet to come frameworks that request greater security, lower idleness, and dependable principles and correspondence limit. One of the critical parts of 5G and 6G innovation is believed to be successful blockage the board. With further developed help quality, it empowers administrator to run many systems administration recreations on a solitary association. To guarantee load adjusting, forestall network cut disappointment, and give substitute cuts in case of blockage or cut frustration, a modern pursuing choices framework to deal with showing up network information is require. Our goal is to balance the strain on BSs while optimizing the value of the information that is transferred from satellites to BSs. Nevertheless, due to their irregular flight characteristic, some satellites frequently cannot establish a connection with Base Stations (BSs), which further complicates the joint satellite-BS connection and channel allocation. SF redistribution techniques based on Deep Reinforcement Learning (DRL) have been devised, taking into account the randomness of the data received by the terminal. In order to predict the best capacity improvements in the wireless instruments of 5G and 6G IoT networks, a hybrid algorithm for deep learning is being used in this study. To control the level of congestion within a 5G/6G network, the suggested approach is put into effect to a training set. With 0.933 accuracy and 0.067 miss rate, the suggested method produced encouraging results.