• Title/Summary/Keyword: network capacity

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Throughput Capacity of a Wireless Multi-hop Relay Network using Cognitive Radio (Cognitive Radio 무선 다중홉 릴레이 네트워크의 Throughput 용량)

  • Hassan, Md. Imrul;Song, Ju-Bin;Kim, Young-Il
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.44 no.5
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    • pp.33-39
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    • 2007
  • In this paper, we investigate the throughput capacity of a multi-hop relay with cognitive radio (CR) enabled relay stations (RS). We suggest a TDMA/FDMA based frame structure where RSs dynamically select unused channels to communicate with the base station (BS) using CR techniques to analyze the throughput capacity. We develop the throughput capacity model for the proposed system based on utilization factor. The analytical results based on those equations show significant improvement in throughput capacity for CR enabled multi-hop relay system.

A Study of Dynamic Forecast on Port Container Handling Capacity (항만 컨테이너 처리능력의 통계적 예측에 관한 연구)

  • Feng, Zhan-Qing;Lee, Su-Ho
    • Journal of Navigation and Port Research
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    • v.26 no.2
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    • pp.161-166
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    • 2002
  • In view of the great disparity between forecasts of Shanghai port container handling capacity and its real results, we choose a dynamic forecast method by the causality model dynamic compensation to predict Shanghai port container handling capacity. And we forecast Shanghai port container handling capacity by using this method. We have made a satisfactory achievement, which provides a more reliable and practical way to forecast container handling capacity.

A Study on The Fuzzy Maximal Flow (퍼지최대흐름에 관한 연구)

  • Sin Jae-Hwan;Kim U-Yeol
    • Journal of the military operations research society of Korea
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    • v.18 no.2
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    • pp.56-65
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    • 1992
  • In the existing deterministic network, the capacity of each arc has been assumed to have a determined property. In reality it may have a property which cannot be determined, and even if it is determined, it contains many errors. Fuzzy theory is efficient in dealing with these kinds of properties. The object of this study is to show that the capacity of each arc and the goal quantity have fuzziness and to develop a new method of determining the fuzzy maximal flow quantity.

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Performance Analysis of HDR-WPAN System with MIMO Techniques (MIMO 기법을 적용한 HDR-WPAN 시스템의 성능분석)

  • Han Deog-Su;Kang Chul-Gyu;Oh Chang-Heon;Cho Sung-Joon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.8
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    • pp.1502-1509
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    • 2006
  • In this paper, we proposed reliability and capacity enhancement methods for IEEE 802.15.3 HDR-WPAN (High Data Rate-Wireless Personal Area Network) system which is currently getting an interest in home network technology adopting a MIMO technique. We also analyzed performance or the proposed system through a computer simulation. The HDR-WPAN system using V-BLAST algorithm, transmitting the different signal vector to each other's sub-channel, can get the transmission speed of more than 110Mbps using two Tx/Px antenna without bandwidth expansion in TCM-64QAM mode. Also the proposed system has reliability of 104 at $E_b/N_0=35dB$ under the Rayleigh fading channel in case of two Tx/Rx antenna with MMSE algorithm. The HDR-WPAN system adopting V-BLAST method has its drawback which is very complicated to determine the decision-ordering at the receiver. But, the proposed system enhances the transmission capacity and reliability without extra bandwidth expansion by sending data streams to multiple antennas.

An Efficient Deep Learning Based Image Recognition Service System Using AWS Lambda Serverless Computing Technology (AWS Lambda Serverless Computing 기술을 활용한 효율적인 딥러닝 기반 이미지 인식 서비스 시스템)

  • Lee, Hyunchul;Lee, Sungmin;Kim, Kangseok
    • KIPS Transactions on Software and Data Engineering
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    • v.9 no.6
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    • pp.177-186
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    • 2020
  • Recent advances in deep learning technology have improved image recognition performance in the field of computer vision, and serverless computing is emerging as the next generation cloud computing technology for event-based cloud application development and services. Attempts to use deep learning and serverless computing technology to increase the number of real-world image recognition services are increasing. Therefore, this paper describes how to develop an efficient deep learning based image recognition service system using serverless computing technology. The proposed system suggests a method that can serve large neural network model to users at low cost by using AWS Lambda Server based on serverless computing. We also show that we can effectively build a serverless computing system that uses a large neural network model by addressing the shortcomings of AWS Lambda Server, cold start time and capacity limitation. Through experiments, we confirmed that the proposed system, using AWS Lambda Serverless Computing technology, is efficient for servicing large neural network models by solving processing time and capacity limitations as well as cost reduction.

Interference Aware Receiver Filtering for Wireless Ad Hoc Networks (무선 애드혹 네트워크에서의 간섭 제어 수신 기법)

  • Shin, Sungpil;Lee, Byungju;Park, Sunho;Shim, Byonghyo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.3
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    • pp.9-15
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    • 2013
  • Recent works on ad hoc network study have shown that achievable throughput can be made to scale linearly with the number of receive antennas even if the transmitter has only a single antenna. In this paper, we propose a non-parametric linear minimum mean square error (MMSE) receiver for achieving further gain in performance when the channel state information at receiver (CSIR) of interferers is imperfect. The key feature to make our approach effective is to exploit the autocorrelation of the received signal. In fact, by incorporating the desired channel information on top of the observations including interference and noise only, the proposed method achieves large fraction of the optimal MMSE transmission capacity without transmission rate loss. From the SINR analysis as well as transmission capacity simulations in realistic ad hoc network system, we show that the proposed non-parametric linear MMSE receiver brings substantial performance gain over existing multiple receive antenna algorithms.

A Tree based Channel Assignment Protocol for Considering the Performance Anomaly in IEEE 802.11 Wireless Mesh Networks (IEEE 802.11 무선 메쉬 네트워크에서의 성능 이상 현상 고려를 위한 트리 기반 채널 할당 프로토콜)

  • Kim, Sok-Hyong;Kim, Dong-Wook;Suh, Young-Joo
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.3
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    • pp.341-345
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    • 2010
  • WMN is one of efficient solutions to provide Internet services for users by forming wireless backbone networks with wireless links. The dominant technology for WMNs is the IEEE 802.11, which provides multi-channel and multi-rate capabilities. One of important issues in WMNs is the network capacity and it is essential to design a multi-channel protocol that leverages the network capacity. However, when wireless links that use different data rates operate on the common channel, the performance of high-rate links is severely degraded by the presence of the low-rate links, which is often referred as performance anomaly. In this paper, we propose a Tree-based Channel Assignment (TreeCA) protocol to mitigate the performance anomaly problem by distributing data rates over multiple channels. TreeCA performs channel assignments based on the tree WMN architecture to accommodate the Internet traffics efficiently. Parent nodes on the tree distribute their child nodes over multiple channels so that the performance anomaly is reduced. Through simulations, we observed that the proposed TreeCA outperforms the existing multi-channel protocols for WMNs.

Power Splitting-based Analog Network Coding for Improving Physical Layer Security in Energy Harvesting Networks (에너지 하베스팅 네트워크에서 물리계층 보안을 향상시키기 위한 파워 분할 기반의 아날로그 네트워크 코딩)

  • Lee, Kisong;Choi, Hyun-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.10
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    • pp.1849-1854
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    • 2017
  • Recently, RF energy harvesting, in which energy is collected from the external RF signals, is considered as a promising technology to resolve the energy shortage problem of wireless sensors. In addition, it is important to guarantee secure communication between sensors for implementing Internet-of-Things. In this paper, we propose a power splitting-based network analog coding for maximizing a physical layer security in 2-hop networks where the wireless-powered relay can harvest energy from the signals transmitted by two sources. We formulate systems where two sources, relay, and eavesdropper exist, and find an optimal power splitting ratio for maximizing the minimum required secrecy capacity using an exhaustive search. Through simulations under various environments, it is demonstrated that the proposed scheme improves the minimum required secrecy capacity by preventing the eavesdropper from overhearing source signals, compared to the conventional scheme.

An Empirical Study on Machine Learning based Smart Device Lithium-Ion Cells Capacity Estimation (머신러닝 기반 스마트 단말기 Lithium-Ion Cell의 잔량 추정 방법의 실증적 연구)

  • Jang, SungJin
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.4
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    • pp.797-802
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    • 2020
  • Over the past few years, smart devices, including smartphones, have been continuously required by users based on portability. The performance is improving. Ubiquitous computing environment and sensor network are also improved. Due to various network connection technologies, mobile terminals are widely used. Smart terminals need technology to make energy monitoring more detailed for more stable operation during use. The smart terminal which is light in small size generates the power shortage problem due to the various multimedia task among the terminal operation. Various estimation hardwares have been developed to prevent such situation in advance and to operate stable terminals. However, the method and performance of estimating the remaining amount are not relatively good. In this paper, we propose a method for estimating the remaining amount of smart terminals. The Capacity Estimation of lithium ion cells for stable operation was estimated based on machine learning. Learning the characteristics of lithium ion cells in use, not the existing hardware estimation method, through a map learning algorithm using machine learning technique The optimized results are estimated and applied.

Triangulation Algorithm for Multi-user Spatial Multiplexing in MIMO Downlink Channels (MIMO 다운링크 채널에서 다중사용자 공간다중화를 위한 알고리즘)

  • Lee, Heun-Chul;Paulraj, Aroyaswami;Lee, In-Kyu
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.1C
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    • pp.45-54
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    • 2010
  • This paper studies the design of a multiuser multiple-input multiple-output (MIMO) system, where a base station (BS) transmits independent messages to multiple users. The remarkable "dirty paper coding (DPC)" result was first presented by Costa that the capacity does not change if the Gaussian interference is known at the transmitter noncausally. While several implementable DPC schemes have been proposed recently for single-user dirty-paper channels, DPC is still difficult to implement directly in practical multiuser MIMO channels. In this paper, we propose a network channel matrix triangulation (NMT) algorithm for utilizing interference known at the transmitter. The NMT algorithm decomposes a multiuser MIMO channel into a set of parallel, single-input single-output dirty-paper subchannels and then successively employs the DPC to each subchannel. This approach allows us to extend practical single-user DPC techniques to multiuser MIMO downlink cases. We present the sum rate analysis for the proposed scheme. Simulation results show that the proposed schemes approach the sum rate capacity of the multiuser MIMO downlink at moderate signal-to-noise ratio (SNR) values.