• Title/Summary/Keyword: 무선 셀룰러 망

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Prediction Accuracy Enhancement Based on Adaptive Reporting Schemes of Mobile's Mobility Status Information (적응형 이동정보 보고 알고리즘에 기반한 무선 단말의 이동성 예측 정확도 향상 방안)

  • Ko, Yong-Chae;Bae, Jung-Hwa;Park, Jin-Woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.7A
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    • pp.778-784
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    • 2007
  • Predictive channel reservation techniques have widely been studied in mobile cellular networks in order to meet the desired quality-of-service requirements. Those efforts are mostly concentrated on predicting the target cell that a mobile will move to and reserving the channel before the actual handoff, and subsequently reducing handoff-dropping probability and improving bandwidth utilization. In this paper, we propose adaptive reporting schemes that a mobile reports its mobility status information such as position, speed, and direction in an appropriate moment based on the user's mobility pattern characteristics and, hence the network can make a more-accurate prediction on the user's mobility. We show from the simulations that the proposed scheme is capable of keeping target cell prediction more accurate and required number of reporting through the wireless up-link channel lower.

Design and Evaluation of a Rough Set Based Anomaly Detection Scheme Considering Weighted Feature Values (가중 특징 값을 고려한 러프 집합 기반 비정상 행위 탐지방법의 설계 및 평가)

  • Bae, Ihn-Han;Lee, Hwa-Ju;Lee, Kyung-Sook
    • Journal of Korea Multimedia Society
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    • v.9 no.8
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    • pp.1030-1036
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    • 2006
  • The rapid proliferation of wireless networks and mobile computing applications has changed the landscape of network security. Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. This paper presents an efficient rough set based anomaly detection method that can effectively identify a group of especially harmful internal masqueraders in cellular mobile networks. Our scheme uses the trace data of wireless application layer by a user as feature value. Based on the feature values, the use pattern of a mobile's user can be captured by rough sets, and the abnormal behavior of the mobile can be also detected effectively by applying a roughness membership function considering weighted feature values. The performance of our scheme is evaluated by a simulation. Simulation results demonstrate that the anomalies are well detected by the method that assigns different weighted values to feature attributes depending on importance.

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A combination of periodic and on-demand scheduling for data broadcasting in mobile convergence networks (모바일 융합망에서 주기적방법과 on-demand 방법을 결합한 데이터 방송 스케줄링 기법)

  • Kang, Sang-Hyuk;Ahn, Hee-June
    • Journal of Broadcast Engineering
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    • v.14 no.2
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    • pp.189-196
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    • 2009
  • We propose a hybrid broadcast scheduling based on a combination of periodic and on-demand data scheduling methods for mobile data broadcasting in convergence networks from communication and broadcasting. We consider an environment in which the forward channel is for data broadcasting and the reverse channel is for sending data requests via cellular phones, WLAN, WiBro, etc. Collecting statistics of requests from clients, the server partitions the data items into hot-item and cold-item sets. Hot items are sent based on a push-based scheduling. An on-demand scheduling method is applied to cold items. Performance evaluation from simulations shows that our proposed scheduling algorithm yields small response time with high successful response ratio.

Path Loss Prediction Using an Ensemble Learning Approach

  • Beom Kwon;Eonsu Noh
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.2
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    • pp.1-12
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    • 2024
  • Predicting path loss is one of the important factors for wireless network design, such as selecting the installation location of base stations in cellular networks. In the past, path loss values were measured through numerous field tests to determine the optimal installation location of the base station, which has the disadvantage of taking a lot of time to measure. To solve this problem, in this study, we propose a path loss prediction method based on machine learning (ML). In particular, an ensemble learning approach is applied to improve the path loss prediction performance. Bootstrap dataset was utilized to obtain models with different hyperparameter configurations, and the final model was built by ensembling these models. We evaluated and compared the performance of the proposed ensemble-based path loss prediction method with various ML-based methods using publicly available path loss datasets. The experimental results show that the proposed method outperforms the existing methods and can predict the path loss values accurately.

A Wireless Traffic Load-Balancing Algorithm based on Adaptive Bandwidth Reservation Scheme in Mobile Cellular Networks (셀룰러 망에서 적응적 대역폭 예약 기법을 이용한 무선 트래픽 부하 균형 알고리즘)

  • 정영석;우매리;김종근
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2001.06a
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    • pp.21-24
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    • 2001
  • For very large multimedia traffic to be supported successfully in wireless network environment, it is necessary to provide Quality-of-Service(QoS) guarantees between mobile hosts(clients). In order to guarantee the Qos, we have to keep the call blocking probability below target value during handoff session. However, the QoS negotiated between the client and the network may not be guaranteed due to lack of available channels for traffic in the new cell, since mobile clients should be able to continue their on-going sessions. In this paper we propose a efficient load-balancing algorithm based on the adaptive bandwidth reservation scheme for enlarging available channels in a cell. We design a new method to predict the mobility of clients using MPT(mobility profile table). This method is then used to reserve a part of bandwidths for handoff calls to its adjacent cells and this reserved bandwidth can be used for handoff call prior to new connection requests. If the number of free channels is also under a low threshold value, our scheme use a load-balancing algorithm with a adaptive bandwidth reservation. In order to evaluate the performance of our algorithm, we measure the metrics such as the blocking probability of new calls and dropping probability of handoff calls, and compare with other existing schemes.

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Average Data Rate Analysis for Data Exchanging Nodes via Relay by Concurrent Transmission (데이타 교환 노드의 동시 전송 릴레이 이용을 위한 평균 데이터 전송률 분석)

  • Kwon, Taehoon
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.6
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    • pp.638-644
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    • 2018
  • Relay systems have recently gained attentions because of its capability of cell coverage extension and the power gain as the one of key technologies for 5G. Relays can be exploited for small-cell base stations and the autonomous network, where communication devices communicate with each other cooperatively. Therefore, the relay technology is expected to enable the low power and large capacity communication. In order to maximize the benefits of using a limited number of relays, the efficient relay selection method is required. Especially, when two nodes exchange their data with each other via relay, the relay selection can maximize the average data rate by the spatial location of the relay. For this purpose, the average data rate is analyzed first according to the relay selection. In this paper, we analyzed the average data rate when two nodes exchange their data via dual-hop decode and forward relaying considering the interference by the concurrent transmission under Nakagami-m fading channel. The correctness of the analysis is verified by the Monte Carlo simulation. The results show that the concurrent transmission is superior to the non-concurrent transmission in the high required data rate region rather than in the low required data rate region.