• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.596-599
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• 2004

We propose an Alamouti-like scheme for combining space-time block coding with single-carrier frequency-domain equalization(SC-FDE) in fixed broadband wireless access environment. With two transmit antennas, the scheme is shown to achieve significant diversity gains at low complexity over frequency-selective fading channels

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.142-152
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• 2014

Vehicular Ad-hoc Networks (VANETs) are comprised of wireless mobile nodes characterized by a randomly changing topology, high mobility, availability of geographic position, and fewer power constraints. Orthogonal Frequency Division Multiplexing (OFDM) is a promising candidate for the physical layer of VANET because of the inherent characteristics of the spectral efficiency and robustness to channel impairments. The susceptibility of OFDM to Inter-Carrier Interference (ICI) is a challenging issue. The high mobility of nodes in VANET causes higher Doppler shifts, which results in ICI in the OFDM system. In this paper, a frequency domain com-btype channel estimation was used to cancel out ICI. The channel frequency response at the pilot tones was estimated using a Least Square (LS) estimator. An efficient interpolation technique is required to estimate the channel at the data tones with low interpolation error. This paper proposes a robust interpolation technique to estimate the channel frequency response at the data subcarriers. The channel induced noise tended to degrade the Bit Error Rate (BER) performance of the system. Parallel concatenated Convolutional codes were used for error correction. At the decoding end, different decoding algorithms were considered for the component decoders of the iterative Turbo decoder. A performance and complexity comparison among the various decoding algorithms was also carried out.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.676-684
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• 2008

In digital video broadcasting-terrestrial (DVB-T), which is the European digital terrestrial television standard, the orthogonal frequency division multiplexing (OFDM) has been adopted for signal transmission. The main reasons using OFDM are to increase the robustness against the frequency selective fading and impulse noise, and to use available bandwidth efficiently. However, channel variation within an OFDM symbol destroys orthogonality between subcarriers, resulting in inter-carrier interference (ICI), which increases an error floor in proportional to maximum Doppler spread. This paper provides an ICI analysis in both time and frequency domains while existing literatures analyze the ICI effects mainly in frequency domain and proposes the algorithms that estimate the channel impulse response and channel variation using least square (LS) algorithm which is the most simple channel estimation technique. And we propose adaptive channel estimation algorithm that estimates the velocity of terminals. The simulation results show that proposed algorithm has similar performance with about 1.5% computational complexity of noise and ICI reduction LS algorithm in low speed environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.241-248
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• 2007

In predictive image coding, a LS (Least Squares)-based adaptive predictor is an efficient method to improve image edge predictions. This paper proposes a hybrid interpolation with weighted edge detector. A hybrid approach of switching between bilinear interpolation and EDI (Edge-Directed Interpolation) is proposed in order to reduce the overall computational complexity The objective and subjective quality is also similar to the bilinear interpolation and EDI. Experimental results demonstrate that this hybrid interpolation method that utilizes a weighted edge detector can achieve reduction in complexity with minimal degradation in the interpolation results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.183-189
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• 2013

This paper proposes a novel lossless image compression scheme composed of direction-adaptive prediction and context-based entropy coding. In the prediction stage, we analyze the directional property with respect to the current coding pixel and select an appropriate prediction pixel. In order to further reduce the prediction error, we propose a prediction error compensation technique based on the context model defined by the activities and directional properties of neighboring pixels. The proposed scheme applies a context-based Golomb-Rice coding as the entropy coding since the coding efficiency can be improved by using the conditional entropy from the viewpoint of the information theory. Experimental results indicate that the proposed lossless image compression scheme outperforms the low complexity and high efficient JPEG-LS in terms of the coding efficiency by 1.3% on average for various test images, specifically for the images with a remarkable direction the proposed scheme shows better results.