• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3498-3511
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• 2016

We investigate the channel state information (CSI) in multi-input multi-output (MIMO) cooperative networks that employ the amplify-and-forward transmission scheme. Least squares and expectation conditional maximization have been proposed in the system. However, neither of these two approaches takes advantage of channel sparsity, and they cause estimation performance loss. Unlike linear channel estimation methods, several compressed channel estimation methods are proposed in this study to exploit the sparsity of the MIMO cooperative channels based on the theory of compressed sensing. First, the channel estimation problem is formulated as a compressed sensing problem by using sparse decomposition theory. Second, the lower bound is derived for the estimation, and the MIMO relay channel is reconstructed via compressive sampling matching pursuit algorithms. Finally, based on this model, we propose a novel algorithm so called sparsity adaptive expectation maximization (SAEM) by using Kalman filter and expectation maximization algorithm so that it can exploit channel sparsity alternatively and also track the true support set of time-varying channel. Kalman filter is used to provide soft information of transmitted signals to the EM-based algorithm. Various numerical simulation results indicate that the proposed sparse channel estimation technique outperforms the previous estimation schemes.

• Current Optics and Photonics
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• v.8 no.3
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• pp.215-224
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• 2024

In medium- and long-range optical imaging systems, atmospheric turbulence causes blurring and distortion of images, resulting in loss of image information. An image-restoration method based on an adaptive feature-fusion multi-input-multi-output (MIMO) dense U-shaped network (Unet) is proposed, to restore a single image degraded by atmospheric turbulence. The network's model is based on the MIMO-Unet framework and incorporates patch-embedding shallow-convolution modules. These modules help in extracting shallow features of images and facilitate the processing of the multi-input dense encoding modules that follow. The combination of these modules improves the model's ability to analyze and extract features effectively. An asymmetric feature-fusion module is utilized to combine encoded features at varying scales, facilitating the feature reconstruction of the subsequent multi-output decoding modules for restoration of turbulence-degraded images. Based on experimental results, the adaptive feature-fusion MIMO dense U-shaped network outperforms traditional restoration methods, CMFNet network models, and standard MIMO-Unet network models, in terms of image-quality restoration. It effectively minimizes geometric deformation and blurring of images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.1044-1051
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• 2010

In this paper, we propose an efficient soft-output signal detection method for spatially multiplexed multiple input multiple output (MIMO) systems. The proposed method is based on the ordered successive interference cancellation (OSIC) algorithm, but it significantly improves the performance of the original OSIC algorithm by solving the error propagation problem. The proposed method combines this enhanced OSIC (ESIC) algorithm with a multiple ordering technique in a very efficient way. As a result, the log likelihood ratio (LLR) values can be computed by using a very small set of candidate symbol vectors. The proposed method has been implemented with a $0.13{\mu}m$ CMOS technology for a $4{\times}4$ 16-QAM MIMO system. The simulation and implementation results show that the proposed detector provides a very good solution in terms of performance and hardware complexity.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.5
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• pp.30-37
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• 2015

The study for enhancing the data transmission rate of the next generation wireless communication system using MIMO system operating in the frequency selective fading environment is currently actively conducted. Mixed signal from each transmitted antennas are received at antennas. The training signal with orthogonal property is needed to separate the mixed signal and enable to estimate channel and time synchronization. In this paper we introduce several training sequences used in MIMO communication system and proposed the modified WeCAN sequence with good auto-correlation property in interested area. We compared auto-correlation property of each sequence via simulation and compared the performance of sequences in doppler shift and multipath fading channel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1502-1509
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• 2006

In this paper, we proposed reliability and capacity enhancement methods for IEEE 802.15.3 HDR-WPAN (High Data Rate-Wireless Personal Area Network) system which is currently getting an interest in home network technology adopting a MIMO technique. We also analyzed performance or the proposed system through a computer simulation. The HDR-WPAN system using V-BLAST algorithm, transmitting the different signal vector to each other's sub-channel, can get the transmission speed of more than 110Mbps using two Tx/Px antenna without bandwidth expansion in TCM-64QAM mode. Also the proposed system has reliability of 104 at $E_b/N_0=35dB$ under the Rayleigh fading channel in case of two Tx/Rx antenna with MMSE algorithm. The HDR-WPAN system adopting V-BLAST method has its drawback which is very complicated to determine the decision-ordering at the receiver. But, the proposed system enhances the transmission capacity and reliability without extra bandwidth expansion by sending data streams to multiple antennas.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.4
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• pp.77-85
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• 2009

This paper proposes an efficient system level simulation method for MIMO-OFDM based system in the multi-cell environment. The proposed method analyzes effects of the cell structure, radio channel characteristics and user mobility. The user mobility effect on the system level performance is considered in both channel gain and distance. The receiver SINR calculation procedure is presented in the system which adopts MIMO-OFDM scheme under various system environments. This method can be flexibly extensible to various system environments and provides computationally efficient system level simulation technique which utilizes link level performance analysis. Extensive computer simulations results are presented to obtain the system performance in the various mobile cellular channels using the proposed method. Also this results are analyzed based on the packet error rate for different distances between the base station located in the center of the cell and the mobile user.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.460-468
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• 2009

Multiple-input multiple-output (MIMO) technology applied with orthogonal frequency division multiplexing (OFDM) is considered as the ultimate solution to increase channel capacity without any additional spectral resources. At the receiver side, the challenge resides in designing low complexity detection algorithms capable of separating independent streams sent simultaneously from different antennas. In this paper, we introduce an upper-lower bounded-complexity QRD-M algorithm (ULBC QRD-M). In the proposed algorithm we solve the problem of high extreme complexity of the conventional sphere decoding by fixing the upper bound complexity to that of the conventional QRD-M. On the other hand, ULBC QRD-M intelligently cancels all unnecessary hypotheses to achieve very low computational requirements. Analyses and simulation results show that the proposed algorithm achieves the performance of conventional QRD-M with only 26% of the required computations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2C
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• pp.86-92
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• 2011

This paper details the downlink performance analysis of an multiple antennas system that combines adaptive beamforming and spatial multiplexing (SM) Multiple Input Multiple Output (MIMO). The combination of MIMO signal processing with adaptive beamforming is applied to WiBro, the South Korean Orthogonal Frequency Division Multiple Access (OFDMA) system that follows the IEEE 802.16e standard. Performance analysis is based on the results of experiments and simulations obtained from a fixed-point simulation testbed. Simulations demonstrate that the MIMO Beamforming OFDMA system improves the required signal to noise ratio (SNR) over the conventional MIMO OFDMA system by 3 dB (QPSK) / 2.5 dB (16-QAM) for the frame error rate (FER) of 1% in the WiBro signal environments. From the implementation of the fixed-point simulation testbed and its experimental results, we verify the feasibility of the MIMO Beamforming technology for realizing a practical WiBro base station.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.77-82
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• 2015

Recently, multi-user massive MIMO (MU-Massive MIMO) network has attracted a lot of attention as a technology to accommodate explosively increasing mobile data traffic. However, the MU-Massive MIMO network causes a tremendous hardware complexity in a base station and computational complexity to select optimal set of users. In this paper, we thus propose a simple algorithm for selecting antennas and users while reducing the hardware and computational complexities simultaneously. The proposed scheme has a computational complexity of $O((N-S_a+1){\times}min(S_a,K))$, which is significantly reduced compared to the complexity of optimal scheme based on Brute-Force searching, $$O\left({_N}C_S_a\sum_{i=1}^{min(S_a,K)}_KC_i\right)$$, where N, $S_a$, and K denote the number of total transmit antennas, the number of selected antennas, and the number of all users, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2647-2662
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• 2014

This paper proposes an efficient and low complexity power-loading algorithm for MIMO-OFDM downlink based cognitive radio system that maximizes the sum rate of single secondary user (SU) under constraints on the tolerable interference thresholds between secondary user and primary user's frequency bands and the total transmission power. Our suboptimal algorithm is based on the $2^{nd}$ order interference tracking and nulling mechanism to allocate transmission power of the subcarriers among SU's scheme. The performance of our proposed suboptimal scheme is compared with the performance of the classical power loading algorithms, e.g., water filling, $1^{st}$ order interference tracking, nulling, and other suboptimal schemes. Numerical results show that our algorithm has low complexity but obtains a higher channel capacity than that of some previous suboptimal algorithms in some scenarios. We dedicate also that for a given interference threshold, the $2^{nd}$ order interference tracking mechanism has dynamic number of nulling position instead fixed number of nulling position.