• Journal of Digital Contents Society
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• v.15 no.2
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• pp.147-154
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• 2014

There have been company researches for TCP-Westwood algorithms in wireless TCP environment with high packet loss rate. Because the TCP-Westwood algorithm adjusts the congestion window according to the ABE(Available Bandwidth Estimation), the algorithm has a problem which the accuracy of ABE decreases as the error rate increases. To solve such a problem, the proposed scheme in this paper adopts the existing packet pattern based algorithm that the ABE is ignored when the arriving interval time of ACK is longer than a given interval time and uses new algorithm that the ABE is reallocated to a given allowable ABE when the ABE is over the allowable range. The proposed scheme shows the simulation result that the ABE is closest to the setting bandwidth for simulation compared to the existing algorithms.

• Journal of the Korean Society for Railway
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• v.16 no.6
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• pp.540-550
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• 2013

The Future Wireless Railway Communication System(FWRCS) has attracted attention for the various advantages of such a system like efficient management, precise periodicity of operation and speedy travel. Related to it, the area of bandwidth requirement estimation for the FWRCS is being researched actively because there is a great need for accurate bandwidth distribution. In this paper, sophisticated bandwidth requirement estimation method for FWRCS is proposed by modifying ITU-R M.1390. With this method, the expected frequency requirements for the present, for five years from now, and for 10 years from now can be calculated by applying the data gathered from the actual field.

• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.19-27
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• 1998

We considered the bandwidth selection method which has asymptotic optimal convergence rate $n^{-1/2}$ in kernel regression function estimation. For the proposed bandwidth selection, we considered Mean Averaged Squared Error as a performance criterion and its Taylor expansion to the fourth order. Then we estimate the bandwidth which minimizes the estimated approximate value of MASE. Finally we show the relative convergence rate between optimal bandwidth and proposed bandwidth.

• Journal of the Korean Data and Information Science Society
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• v.3 no.1
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• pp.17-24
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• 1992

The problem of estimating symmetric probability density with high kurtosis is considered. Such densities are often estimated poorly by a global bandwidth kernel estimation since good estimation of the peak of the distribution leads to unsatisfactory estimation of the tails and vice versa. In this paper, we propose a transformation technique before using a global bandwidth kernel estimator. Performance of density estimator based on proposed transformation is investigated through simulation study. It is observed that our method offers a substantial improvement for the densities with high kurtosis. However, its performance is a little worse than that of ordinary kernel estimator in the situation where the kurtosis is not high.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3856-3872
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• 2018

HTTP-based adaptive streaming (HAS) has recently been widely deployed on the Internet. In the HAS system, a video content is encoded at multiple bitrates and the encoded video content is segmented into small parts of fixed durations. The HAS client requests a video segment and stores it in the playout buffer. The rate adaptation algorithm employed in HAS clients dynamically determines the video bitrate depending on the time-varying bandwidth. Many studies have shown that an efficient rate adaptation algorithm is critical to ensuring quality-of-experience in HAS systems. However, existing algorithms have problems estimating the network bandwidth because bandwidth estimation is performed on the client-side application stack. Without the help of transport layer protocols, it is difficult to achieve accurate bandwidth estimation due to the inherent segment-based transmission of the HAS. In this paper, we propose an alternative approach that utilizes the playout buffer occupancy rather than using bandwidth estimates obtained from the application layer. We start with a queueing analysis of the playout buffer. Then, we present a buffer-aware rate adaptation algorithm that is solely based on the mean buffer occupancy. Our simulation results show that compared to conventional algorithms, the proposed algorithm achieves very smooth video quality while delivering a similar average video bitrate.

• Journal of electromagnetic engineering and science
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• v.4 no.1
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• pp.23-29
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• 2004

In this paper we analyze convergence constraints and time constant of IT-LMS algorithm and derive a method of making it's time constant independent of signal power by using input variance estimation. The method for estimating the input variance is to use a single-pole low-pass filter(LPF) with common smoothing parameter value, θ. The estimator is with narrow bandwidth for large θ but with wide bandwidth for small θ. This small θ gives long term average estimation(low frequency) of the fluctuating input variance well as short term variations (high frequency) of the input power. In our simulations of multipath communication channel equalization environments, the method with large θ has shown not as much improved convergence speed as the speed of the original IT-LMS algorithm. The proposed method with small θ=0.01 reach its minimum MSE in 100 samples whereas the IT-LMS converges in 200 samples. This shows the proposed, tap-power normalized IT-LMS algorithm can be applied more effectively to digital wireless communication systems.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.236-241
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• 2022

We consider methods of estimating a binary regression function using a nonparametric kernel estimation when there is only one covariate. For this, the Nadaraya-Watson estimation method using single and double bandwidths are used. For choosing a proper smoothing amount, the cross-validation and plug-in methods are compared. In the real data analysis for case study, German credit data and heart disease data are used. We examine whether the nonparametric estimation for binary regression function is successful with the smoothing parameter using the above two approaches, and the performance is compared.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1490-1500
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• 1996

One of the important issues for multimedia communications over ATM netowrks is efficient use of net-work resources since transmitting video at low cost requires high utilization of channel bandwidth. In this paper, we propose an effective bandwidth estimation scheme for MPEG sources in ATM networks. It has been known difficult to allocate effective transmission bandwidth to MPEG sources due to its bursty charactersitics. The MPEG traffic stream can bemodeled using five traffic parameters:service rate, burst load ratio, interburst load ratio, burst period, and interburst period. Using these parameters, a transmission bandwidth for each source can be estimated, and the estimated bandwidth is applied synchronously to reduce the queue size in a buffer. For a simple network modelof a high speed link that multiplexes a number of virtual-circuit connections, simulations on adaptive bandwidth allocation were performed, and the results show that the queueing delay is significantly reduced, when compared to a fixed bandwidth allocation.

• The Journal of the Acoustical Society of Korea
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• v.26 no.6
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• pp.259-268
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• 2007

This paper contributes to an improvement of the statistical bandwidth extension(BWE) system based on Hidden Markov Model(HMM). First, the existing HMM training method for BWE, which is suggested originally by Jax, is analyzed in comparison with the general Baum-Welch training method. Next, based on this analysis, a new HMM-based BWE method is suggested which adopts the Baum-Welch re-estimation algorithm instead of the Jax's to train HMM model. Conclusionally speaking, the Baum-Welch re-estimation algorithm is a generalized form of the Jax's training method. It is flexible and adaptive in modeling the statistical characteristic of training data. Therefore, it generates a better model to the training data, which results in an enhanced BWE system. According to experimental results, the new method performs much better than the Jax's BWE systemin all cases. Under the given test conditions, the RMS log spectral distortion(LSD) scores were improved ranged from 0.31dB to 0.8dB, and 0.52dB in average.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.765-775
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• 2012

The cross-validation is a popular method to select bandwidth in all types of kernel estimation. The maximum likelihood cross-validation, the least squares cross-validation and biased cross-validation have been proposed for bandwidth selection in kernel density estimation. In the case that the probability density function has a discontinuity point, Huh (2012) proposed a method of bandwidth selection using the maximum likelihood cross-validation. In this paper, two forms of cross-validation with the one-sided kernel function are proposed for bandwidth selection to estimate the location and jump size of the discontinuity point of density. These methods are motivated by the least squares cross-validation and the biased cross-validation. By simulated examples, the finite sample performances of two proposed methods with the one of Huh (2012) are compared.