• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.979-982
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• 2002

Compressing image data by using Vector Quantization (VQ)［1］-［3］will compare Training Vectors with Codebook. The result is an index of position with minimum distortion. The implementing Random Codebook will reduce the image quality. This research presents the Splitting solution ［4］,［5］to implement the Codebook, which improves the image quality［6］by the average Training Vectors, then splits the average result to Codebook that has minimum distortion. The result from this presentation will give the better quality of the image than using Random Codebook.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2086-2097
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• 2012

A terminal-based dynamic clustering algorithm is proposed in a multi-cell scenario, where the user could select the cooperative BSs from the predetermined static base stations (BSs) set based on dynamic channel condition. First, the user transmission rate is derived based on linear precoding and per-cell feedback scheme. Then, the dynamic clustering algorithm can be implemented based on two criteria: (a) the transmission rate should meet the user requirement for quality of service (QoS); (b) the rate increment exceeds the predetermined constant threshold. By adopting random vector quantization (RVQ), the optimized number of cooperative BSs and the corresponding channel conditions are presented respectively. Numerical results are given and show that the performance of the proposed method can improve the system resources utilization effectively.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3150-3152
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• 1999

The efficient representation and encoding of signals with limited resources, e.g., finite storage capacity and restricted transmission bandwidth, is a fundamental problem in technical information processing systems. Typically under realistic circumstances, the encoding and communication of message has to deal with different sources of noise and disturbances. In this paper, I propose a unifying approach to data compression by robust vector quantization, which explicitly deals with channel noise, and random elimination of prototypes. The resulting algorithm is able to limit the detrimental effect of noise in a very general communication scenario. In this paper, based on the robust vector quantization I have an experiment about speech coding.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.107-115
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• 1996

The average distortio of the vector quantizer is calcualted using a probability function F of the input source for a given codebook. But, since the input source is unknown in geneal, using the sample vectors that is realized from a random vector having probability function F, a time-average opeation is employed so as to obtain an approximation of the average distortion. In this case the size of the smple set should be large so that the sample vectors represent true F reliably. The theoretical inspection about the approximation, however, is not perfomed rigorously. Thus one might use the time-average distortion without any verification of the approximation. In this paper, the convergence characteristics of the time-average distortions are theoretically investigated when the size of sample vectors or the size of codebook gets large. It has been revealed that if codebook size is large enough, then small sample set is enough to obtain the average distortion by approximatio of the calculated tiem-averaged distortion. Experimental results on synthetic data, which are supporting the analysis, are also provided and discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.628-636
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• 2015

In this paper, we propose a non-convex compressed sensing(NCCS)-based channel state information(CSI) feedback scheme for massive multiple-input multiple-output(MIMO) systems. Combining the random vector quantization(RVQ), the proposed scheme permits a transmitter to obtain CSI with acceptable accuracy under substantially reduced feedback load. Furthermore, it recovers CSI from fewer measurements than that of existing convex compressed sensing(CCS)-based schemes even if the measurements are inaccurate and incomplete. Simulation results show that the proposed scheme achieves higher throughput than both existing CCS-based feedback scheme and random vector quantization(RVQ) feedback scheme with the same feedback load.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.26-32
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• 2007

In sequential speaker classification, the lack of prior information about the speakers poses a challenge for model initialization. To address the challenge, a predetermined generic model set, called Sample Speaker Models, was previously proposed. This approach can be useful for accurate speaker modeling without requiring initial speaker data. However, an optimal method for sampling the models from a generic model pool is still required. To solve this problem, the Speaker Quantization method, motivated by vector quantization, is proposed. Experimental results showed that the new approach outperformed the random sampling approach with 25% relative improvement in error rate on switchboard telephone conversations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.7
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• pp.431-436
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• 2014

In this paper, we propose a compressive sensing-based channel quantization feedback mechanism that is appropriate for practical massvie multiple-input multiple-output (MIMO) systems. We assume that the base station (BS) has a compact uniform square array that has a highly correlated channel. To serve multiple users, the BS uses a zero-forcing precoder. Our proposed channel feedback algorithm can reduce the feedback overhead as well as a codebook search complexity. Numerical simulations confirm our analytical results.

• Convergence Security Journal
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• v.6 no.4
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• pp.83-90
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• 2006

In this paper, we propose a new design method for a robust vector quantizer that is independent of the statistical characteristics of input images in the wavelet transformed image coding. The conventional vector quantizers have failed to get quality coding results because of the different statistical properties between the image to be quantized and the training sequence for a codebook of the vector quantizer. Therefore, in order to solve this problem, we used a pseudo image as a training sequence to generate a codebook of the vector quantizer; the pseudo image is created by adding correlation coefficient and edge components to uniformly distributed random numbers. We will clearly define the problem of the conventional vector quantizers, which use real images as a training sequence to generate a codebook used, by comparing the conventional methods with the proposed through computer simulation. Also, we will show the proposed vector quantizer yields better coding results.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.46-55
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• 1995

In this paper, we present a new wavelet transform-based CELP coder, called band selection wavelet transform CELP (BS-WTCELP) operated at 4.8 kbps. The proposed algorithm uses a band selection scheme of frequency bands of wavelet transform and selective vector quantization (VQ). The band selection and selective VQ structure is implemented by using a classified VQ structure. The proposed algorithm has about 0.5-1.0 dB improvement in segmental SNR compared with the conventional CELP that uses the random codebook search, while is has significantly reduced computational and storage complexity. Many experimental results have shown that the proposed algorithm is more suitable for most real-applications than the conventional CELP and wavelet transform CELP.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.736-741
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• 2009

In this paper, adaptive optimizations of precoder codebook to channel conditions is proposed for a multiuser multiple-input multiple-output (MIMO) system with split linear array and limited feedback. We propose adaptive method for constructing a precoder codebook by coloring the random vector quantization codebook at each link by using limited long-term feedback information on transmit correlation matrix of each link. It is shown that the proposed multiuser MIMO codebook design scheme outperforms existing multiuser MIMO codebook design schemes for various channel conditions in terms of the average sum throughput of multiuser MIMO systems using zero-forcing maximum eigenmode transmission and limited feedback.