• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3A
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• pp.260-268
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• 2010

Channel inversion is one of the simplest techniques for multiuser downlink systems with single-antenna users. In this paper, we extend the regularized channel inversion technique developed for the single-antenna user case to multiuser multiple-input multiple-output (MIMO) channels with multiple-antenna users. We first employ the multiuser preprocessing to project the multiuser signals near the null space of the unintended users based on the MMSE criterion, and then the single-user preprocessing is applied to the decomposed MIMO interference channels. In order to reduce the complexity, we focus on non-iterative solutions for the multiuser transmit beamforming and use a linear receiver based on an MMSE criterion. Simulation results show that the proposed scheme outperforms existing joint iterative algorithms in most multiuser configurations.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.1
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• pp.21-28
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• 2004

In this paper we apply block turbo coding at the transmitter and iterative decoding algorithm at the receiver for different operating modes, based on the 5 ㎓ IEEE 802.1 la WLAN system, instead of convolutional coding and soft decision viterbi algorithm to improve forward error correcting performance. Experimental results showed that each coding scheme outperforms coding gains of up to 3.5 ㏈ at the BER of 10$\^$-3/.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4160-4176
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• 2015

Data compression like image and video compression has come a long way since the introduction of Compressive Sensing (CS) which compresses sparse signals such as images, videos etc. to very few samples i.e. M < N measurements. At the receiver end, a robust and efficient recovery algorithm estimates the original image or video. Many prominent algorithms solve least squares problem (LSP) iteratively in order to reconstruct the signal hence consuming more processing time. In this paper non-iterative threshold based recovery algorithm (NITRA) is proposed for the recovery of images and videos without solving LSP, claiming reduced complexity and better reconstruction quality. The elapsed time for images and videos using NITRA is in ㎲ range which is 100 times less than other existing algorithms. The peak signal to noise ratio (PSNR) is above 30 dB, structural similarity (SSIM) and structural content (SC) are of 99%.

• Journal of Korea Multimedia Society
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• v.7 no.6
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• pp.781-790
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• 2004

This paper presents a fourth-order cumulants based iterative algorithm for blind channel equalization. It is robust with respect to the existence of heavy Gaussian noise in a channel and does not require the minimum phase characteristic of the channel. In this approach, the transmitted signals at the receiver are over-sampled to ensure the channel described by a full-column rank matrix. It changes a single-input/single-output (SISO) finite-impulse response (FIR) channel to a single-input/multi-output (SIMO) channel. Based on the properties of the fourth-order cumulants of the over-sampled channel outputs, the iterative algorithm is derived to estimate the deconvolution matrix which makes the overall transfer matrix transparent, i.e., it can be reduced to the identity matrix by simple reordering and scaling. Both a closed-form and a stochastic version of the proposed algorithm are tested with three-ray multi-path channels in simulation studies, and their performances are compared with a method based on conventional second-order cumulants. Relatively good results are achieved, even when the transmitted symbols are significantly corrupted with Gaussian noise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.424-442
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• 2014

Most recent research on iterative solutions for interference alignment (IA) presents solutions assuming channel reciprocity based on the suppression of interference from undesired sources by using an appropriate decoding matrix also known as a receiver combining matrix for multiple input multiple output (MIMO) interference channel networks and reciprocal networks. In this paper, we present an alternative solution for IA by designing precoding and decoding matrices based on the concept of signal leakage (the measure of signal power that leaks to unintended users) on each transmit side. We propose an iterative algorithm for an IA solution based on maximization of the signal-to-leakage-and-noise ratio (SLNR) of the transmitted signal from each transmitter. In order to make an algorithm removing the requirement of channel reciprocity, we deploy maximization of the signal-to-interference-and-noise ratio (SINR) in the design of the decoding matrices. We show through simulation that minimizing the leakage in each transmission can help achieve enhanced performance in terms of aggregate sum capacity in the system.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.32-36
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• 2016

In wireless communication systems, jamming attack is a critical threat. Especially, reactive jamming can jam when the sender and receiver are communicating, which can maximize the attack efficiency of jamming. In this paper, we use the property of multi-input multi-output (MIMO) technology to achieve jamming resilient orthogonal frequency-division multiplexing (OFDM) communications. In particular, we use MIMO interference cancellation to remove the jamming signals strategically. We first investigate the reactive jamming attack model and their impacts on the MIMO-OFDM systems. We then present an iterative channel estimation algorithm that exploits MIMO interference cancellation. Our simulations show various anti-jamming methods and demonstrate the efficiency of our proposed algorithm under the reactive jamming attack.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.338-343
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• 2005

MIMO(Multiple Input Multiple Output) systems are considered as one of the most promising systems for next generation mobile communication systems which require efficient frequency resource utilization as well as high data rate transmissions. BLAST-STTC is the MIMO system which transmits information from many of STTC encoder groups with two transmit antennas and cancels the interference from other groups in receiver. In this paper we propose a reverse-ordered iterative decoding scheme for BLAST-STTC systems which achieve full diversity gain for all groups and improve the performance of interference cancellation, and compare the error performance of the proposed scheme with general schemes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.399-401
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• 2013

In this paper, we present the method to impove the performance by using iterative decoding in LDPC codes with 8-PSK modulation. Iterative decoding is the technique that improve the performance after the input signals of receiver are re-calculated by using the soft decision output of decoder. DVB-S2 system with 8-PSK modulation based on iterative decoding had a better performance than DVB-S2 with 8-PSK modulation over Gaussian channels.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.117-122
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• 2007

For multiple antenna systems, we consider the hybrid iterative detection of the maximum a posteriori probability(MAP) detection and the linear detection such as the minimum-mean-square-error(MMSE) filtering with soft cancelation. We devise methods to obtain both the lower complexity of the linear detection and the superior performance of the MAP detection. Using the a prior probability of the coded bit which is extrinsic of the outer decoder, we compute the threshold of grouping and determine the detection scheme symbol by symbol. Through the simulation results, it is shown that the proposed receiver obtains the superior performance to the MMSE detector and the lower complexity than the MAP detector.

• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.487-492
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• 2013

Underwater acoustic communication has multipath error because of reflection by sea-level and sea-bottom. The multipath of underwater channel causes signal distortion and error floor. In order to improve the performance, it is necessary to employ an iterative coding scheme. Among the iterative coding scheme, turbo codes, LDPC codes and convolutional code based on BCJR algorithm are dominant channel coding schemes in recent. Therefore this paper analyzed the performance of iterative codes based on turbo equalizer with the same coding rate and similar codeword length. The performances of three kinds of iterative codes were evaluated in the environment of underwater acoustic communication channel that are real data collected in Korean east sea. The distance of transmitter and receiver was 5Km and data rate was 1Kbps. As a result, convolutional code based on BCJR algorithm has better performance in underwater channel than turbo codes and LDPC codes.