• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1117-1124
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• 2013

As the recently soaring wireless traffic, small-cell techniques have been actively studied in order to support such a wireless demand for cellular wireless networks. This paper focuses on the inter-cell interference neutralization to resolve the main barrier for implementing small-cell cellular networks. Assuming that each message is delivered to the final destination by the help of base stations or relays, ergodic interference neutralization is proposed, which exploits the time-varying nature of wireless channels. The previous approach based on amplify-and-forward (AF) suffers from severe performance degradation in the low signal-to-noise (SNR) regime due to noise amplification. On the other hand, the proposed interference neutralization based on recently developed compute-and-forward (CF) fixes such a problem and improves the performance in the low SNR regime.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.5
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• pp.21-29
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• 1999

이동횟수 기반 위치갱신 기법에서 고정망과의 접속은 단말 내부의 계수기가 이동횟수 임계치에 이르러 위치갱신이 수행되거나 신규호가 발생할 경우에 행해진다. 그러나 단말의 계수기가 임계치에 이르는 동시에 단말이 이전 위치갱신이 수행된 셀(중앙셀)로 재진입이 발생할 경우 불필요한 위치갱신이 수행된다. [2]에서는 중앙셀로 재진입이 발생하는 경우의 불필요한 위치갱신 수행을 제거하기 위해 중앙셀로 재진입이 발생할 경우 계수기를 영으로 초기화한다. 본 논문에서는 [2]의 기법을 일반화하여 위치갱신 비용을 절약할 수 있는 개선된 기법을 제안한다. 본 기법은 단말이 셀 사이를 이동하는 동안 단말은 자신이 방문한 셀과 이동횟수에 관한 정보를 저장한다. 단말이 이미 방문한 셀로 재진입이 발생할 겨우 이동횟수 계수기를 증가시키는 것이 아니라 이전 방문시 저장하였던 이동횟수로 재조정한다. 이러한 이동회수 계수기의 재조정 방법을 통하여 불필요한 위치갱신과 신호절차를 효과적으로 줄일 수 있다. [2]의 기법은 본 논문에서 제안하는 기법 중에서 중앙셀로 재진입할 때만 계수기를 영으로 재조정하는 특수한 경우에 해당된다. 본 기법이 전체 위치관리 비용을 크게 절약할 수 있음을 증명하기 위해 다양한 환경에서의 성능분석 및 수치적 결과를 통해 알아 본 결과 호 도착 비율당 전체 위치관리 비용이 평균 17-26% 절약됨을 관찰할 수 있었다.

• The KIPS Transactions:PartC
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• v.9C no.6
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• pp.927-934
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• 2002

In order to provide various multimedia services in a wireless network, the call admission control for wireless channels should be resolved at the time of call setup and handoff by moving mobile terminal. In this paper. we propose a reliable DCAC( Distributed Call Admission Control)scheme using virtual cluster concept. The proposed DCAC scheme considers the state of $1^{st}$ and $2^{nd}$ adjacent cells to provide a reliable call handling. The proposed scheme is analyzed by simulations and mathematical methods.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.73-79
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• 2012

This study attempts to analyze changes in land use patterns in a compound urban and agricultural city Kimje-si, using LANDSAT TM imagery and to forecast future changes accordingly. As a new approach to supervised classification, HSB(Hue, Saturation, Brightness)-transformed images were used to select training zones, and in doing so classification accuracy increased by more than 5 percent. Land use changes were forecasted by using a cellular automaton algorithm developed by applying Markov Chain techniques, and by taking into account classification results and GIS data, such as population of the pertinent region by area, DEMs, road networks, water systems. Upon comparing the results of the forecast of the land use changes, it appears that geographical features had the greatest influence on the changes. Moreover, a forecast of post-2030 land use change patterns demonstrates that 21.67 percent of mountain lands in Kimje-si is likely to be farmland, and 13.11 percent is likely to become city areas. The major changes are likely to occur in small mountain lands located in the heart of the city. Based on the study result, it seems certain that forecasting future land use changes can help plan land use in a compound urban and agricultural city to procure food resources.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.6-8
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• 1999

시뮬레이션 환경이나 실제 환경에서 이동 로봇 제어기를 진화 알고리즘으로 만들어내는 연구가 최근 활발하다. 이전의 연구에서는 기존의 단순한 진화 알고리즘이 환경에 제한된 제어기를 만들어 내는 문제점을 해결하기 위한 방법으로 셀룰라 오토마타 기반 신경망의 점증적 진화방법을 제시하였다. 점증적 진화 방법은 초기에 간단한 행동으로 해결할 수 있는 환경에 맞도록 제어기를 진화시킨 다음, 점차 복잡한 행동이 요구되는 환경에서 제어기를 점증적으로 진화시킨다. 실험결과, 점증적 진화의 방법이 좀 더 효율적으로 로봇을 진화시키고 환경의 변화에 보다 강한 것을 알 수 있었다. 그러나 이전연구에서의 점증적 진화 방법은 한 단계에서 진화가 끝난 후 다음 단계로 넘어갈 개체를 사람이 선택해야 하는 문제가 있었다. 본 논문에서는 이러한 문제점을 해결하기 위한 다양한 방법을 제시하고 실험을 통해 그 유용성을 보이고자 한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.255-258
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• 2001

This paper is implementation of cellular automata neural network system which is a living creatures' brain using evolving hardware concept. Cellular automata neural network system is based on the development and the evolution, in other words, it is modeled on the ontogeny and phylogeny of natural living things. The proposed system developes each cell's state in neural network by CA. And it regards code of CA rule as individual of genetic algorithm, and evolved by genetic algorithm. In this paper we implement this system using evolving hardware concept Evolving hardware is reconfigurable hardware whose configuration is under the control of an evolutionary algorithm. We design genetic algorithm process for evolutionary algorithm and cells in cellular automata neural network for the construction of reconfigurable system. The effectiveness of the proposed system is verified by applying it to time-series prediction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2585-2593
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• 1997

Recently a new wireless communication architecture, a Virtual Cellular Network(VCN) was proposed in order to improve the preformance of a wireless network. Unlike a conventional cellular network, the VCN does not use a conventional frequency reuse concep. In the VCN, however, each mobile can use the entire system bandwidth. There is no pre-determined border of cells nor fixed based station for a mobile to communicate with. The performance of the VCN is improved by allowing any mobile to communicate with any port which residues in the virtual cell of the mobile. In this paepr, the Multi Packet Encoding (MPE) is proposed for the VCN uplink in order to improve the unfair throughput and delay caused by the position of the mobiles, and its performance is investigated via computer simulations. The Minimum Group(MG) is proposed for downlink protocol.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.160-166
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• 2002

Since conventional mobile robot control with one module has limitation to solve complex problems, there have been a variety of works on combining multiple modules for solving them. Recently, many researchers attempt to develop mobile robot controllers using artificial life techniques. In this paper, we develop a mobile robot controller using cellular automata based neural networks, where complex tasks are divided to simple sub-tasks and optimal neural structure of each sub-task is explored by genetic algorithm. Neural network modules are combined dynamically using the action selection mechanism, where basic behavior modules compete each other by inhibition and cooperation. Khepera mobile robot simulator is used to verify the proposed model. Experimental results show that complex behaviors emerge from the combination of low-level behavior modules.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2367-2370
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• 2003

A fast pattern classification algorithm with Cellular Parallel Processing Network-based dynamic programming is proposed. The Cellular Parallel Processing Networks is an analog parallel processing architecture and the dynamic programming is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast Pattern classification with optimization is formed. On such CPPN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.465-472
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• 2004

Analog CPPN-based optimal road boundary detection algorithm for autonomous vehicle is proposed. The CPPN is a massively connected analog parallel array processor. In the paper, the dynamic programming which is an efficient algorithm to find the optimal path is implemented with the CPPN algorithm. If the image of road-boundary information is utilized as an inter-cell distance, and goals and start lines are positioned at the top and the bottom of the image, respectively, the optimal path finding algorithm can be exploited for optimal road boundary detection. By virtue of the parallel and analog processing of the CPPN and the optimal solution of the dynamic programming, the proposed road boundary detection algorithm is expected to have very high speed and robust processing if it is implemented into circuits. The proposed road boundary algorithm is described and simulation results are reported.