• ETRI Journal
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• v.46 no.2
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• pp.205-217
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• 2024

We propose a bandwidth prediction approach based on deep learning. The approach is intended to accurately predict the bandwidth of various types of mobile networks. We first use a machine learning technique, namely, the gradient boosting algorithm, to recognize the connected mobile network. Second, we apply a handover detection algorithm based on network recognition to account for vertical handover that causes the bandwidth variance. Third, as the communication performance offered by 3G, 4G, and 5G networks varies, we suggest a bidirectional long short-term memory model with time distribution for bandwidth prediction per network. To increase the prediction accuracy, pretraining and fine-tuning are applied for each type of network. We use a dataset collected at University College Cork for network recognition, handover detection, and bandwidth prediction. The performance evaluation indicates that the handover detection algorithm achieves 88.5% accuracy, and the bandwidth prediction model achieves a high accuracy, with a root-mean-square error of only 2.12%.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.440-445
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• 2016

There is a scheme where secondary users (SU) use predicted spectrum holes for primary users (PU) not to utilize for efficient utilization of the limited spectrum resources in cognitive radio networks. In this paper, we propose an adaptive call admission control framework that minimizes spectrum hopping call dropped probability (SHDP) for satisfying SU quality of service (QoS). The scheme is based on a call admission control (CAC), bandwidth prediction and adaptive bandwidth assignment. The prediction model predicts not only the number of spectrum holes, but requested bandwidth of SU spectrum hopping call, and then the CAC minimizes SHDP via an adaptive bandwidth assignment in resources not being enough for reservation. We bring Wiener prediction model to predict the resources. Simulations are conducted to compare the performance of proposed scheme with an existing, and show its ability of minimizing the SHDP.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.301-303
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• 2004

In this work, we develop on-line traffic prediction algorithm for real-time VBR traffic. There are a number of important issues: (i) The traffic prediction algorithm should exploit the stochastic characteristics of the underlying traffic and (ii) it should quickly adapt to structural changes in underlying traffic. GOP ARIMA model effectively addresses this issues and it is used as basis in our bandwidth prediction. Our prediction model deploy Kalman filter to incorporate the prediction error for the next prediction round. We examine the performance of GOP ARIMA based prediction with linear prediction with LMS and double exponential smoothing. The proposed prediction algorithm exhibits superior performam againt the rest.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.1
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• pp.24-32
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• 2006

In this paper, we proposed the multimedia call admission control algorithm with the bandwidth reservation based on the prediction of wireless terminal's location to guarantee quality of service for multimedia applications in cellular networks. This algorithm aims at minimizing possible errors In predicting the moving direction of terminals using a mobility prediction scheme. This prediction reduces the size of bandwidth reserved redundantly. In order to evaluate the performance of the algorithm, the blocking rate of new calls and the forced termination rate of hand-off calls are measured and compared the results with those of existing schemes. The results of the experiment revealed that the algorithm presented in this paper achieved better performance with lower call blocking rates and forced-termination rates than those of other methods.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.105-107
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• 2006

As internet streaming data increase, transport protocol such as TCP, TGP-Friendly is important to study control transmission rate and share of Internet bandwidth. In this paper, we propose a TCP-Friendly protocol using Neural Network for media delivery over wired Internet which has various traffic size(PTFRC). PTFRC can effectively send streaming data when occur congestion and predict one-step ahead round trip time and packet loss rate. A multi-layer perceptron structure is used as the prediction model, and the Levenberg-Marquardt algorithm is used as a traning algorithm. The performance of the PTFRC was evaluated by the share of Bandwidth and packet loss rate with various protocols.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.415-420
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• 2014

Another crucial issue is a providing secondary user(SU) with the its guaranteed quality of service(QoS) in cognitive radio systems, from the SU view to be allowed to opportunistically utilize the primary user(PU) spectrum on non-interfering. In this paper, we propose a bandwidth reallocation scheme for reducing SU dropping rate through renegotiation of requested channel numbers when available bandwidth is not enough for accepting the spectrum handoff SUs. We categorize SU calls into two types : the first priority and the second priority SU, and the first SU' service is supported by bandwidth reservation based on ARMA prediction model for PU arrivals, while the second SU's bandwidth demands for spectrum handoff is to be reallocated through their renegotiation. Simulation results show that our scheme can improve SU dropping rate and system resource utilization efficiency by bandwidth reallocation.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1002-1012
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• 2019

360VR content requires short latency, such as immediate response to viewers' viewport changes and high quality video delivery. It is necessary to consider efficient transmission that guarantees the QoE(Quality of Experience) of the 360VR contents with limited bandwidth. Several research has been introduced to reduce overall bandwidth consumption by predicting a user's viewport and allocating different bit rates to the area corresponding to the viewport. In this paper, we propose novel viewport prediction scheme that uses sound source location information of 360VR contents as auditory recognition information along with visual recognition information. Also, we propose efficient transmission algorithm by allocating a bit rate properly based on improved viewport prediction. The proposed scheme improves the accuracy of the viewport prediction and provides high quality videos to tiles corresponding to the user's viewpoint within the limited bandwidth.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.89-96
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• 2000

ABR service is defined by ATM Forum and ITU for the efficient use of link bandwidth, and 2-pass service policing is proposed for this service. 2-pass service policing is effective by the real-time measurement of the used bandwidth, and this scheme obtains multiplexing gam and control efficiently ABR traffic as dynamically allocating rate by residual bandwidth information. In this study, we propose the real-time bandwidth prediction scheme for ABR traffic control, as using dynamic rate allocation by available bandwidth information. This study can obtain the simple hardware structure by means of as predicting available bandwidth by the total link bandwidth and the sum of transmission rate on the backlogged state connections.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.208-213
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• 2009

This paper presents an adaptive call admission control(CAC) algorithm based on a target handoff call dropping probability in mobile wireless environments. This method uses a neural network for predicting and reserving the bandwidth demands for handoff calls and new calls. The amount of bandwidth to be reserved is adaptively adjusted by a target value of handoff call dropping probability(CDP). That is, if the handoff CDP exceeds the a target CDP value, the bandwidth to be reserved should be increased to reduce the handoff dropping probability below a target value. The proposed method is intended to prevent from increasing handoff call dropping probability when bandwidth to be reserved is not enough for handoff calls due to an uncertain prediction. Our simulations compare the handoff CDP in proposed CAC with that of an existing CAC. Results show that the proposed method sustains handoff call dropping probability below our target value.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.9
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• pp.1219-1228
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• 1995

In this paper, we propose a dynamic bandwidth allocation scheme for the transmission of VBR video source through ATM based BISDN. In order to efficiently evaluate the required bandwidth, the characteristics of the VBR video sources generated by the MPEG coder are analyzed with variations in the number of GOP and quantizer scale. The required bandwidth for VBR video source is estimated by a prediction algorithm using scene and frame correlations as well as the statistical properties of the VBR video source. Scene correlation represents a strong correlation among the adjacent slices in a frame, and frame correlation represents a strong correlation among the frames. The statistical properties based on the traffic parameters of video sources such as peak rate, average rate, and standard deviation of source are determined through simulation. The performance of the proposed bandwidth allocation scheme is evaluated in terms of the over-allocated bandwidth, bandwidth utilization, and cell loss rate with variations in the quantizer scale and the number of GOP. It is shown that the results of simulation based on the proposed scheme are superior to those of the conventional methods.