• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.507-513
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• 2015

In this paper, we present the bit-error rate (BER) performance of quasi-orthogonal space-time block code (QOSTBC) massive multiple-input multiple-output (MIMO) system employing up to 32 transmit and receive antennas. The QOSTBC, due to its advantages in transmission rate and decoding complexity, is an important transmit diversity scheme for more than 2 transmit antennas. As massive MIMO implies very large number of antennas, practically at least more than 15 antennas, a different number of transmit and receive antennas (i.e. $2{\times}2$, $4{\times}4$, $8{\times}8$, $16{\times}16$ and $32{\times}32$) using QOSTBC for the massive MIMO system are considered. The BER performance of the massive MIMO with antennas up to $32{\times}32$ using BPSK modulation scheme is analyzed. Simulation results show that the full-rate massive MIMO systems with QOSTBC give a significant performance improvement due to increasing diversity effect, compared with previously considered massive MIMO systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.566-568
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• 2014

In this letter, an MMSE based iterative soft decision interference cancellation scheme for massive MIMO systems is proposed. To reduce the complexity, the proposed scheme uses the Sherman-Morrison-Woodbury formula to compute the entire MMSE filtering vectors in one iteration by one matrix inverse operation. Simulation results show that the proposed scheme also has a comparable BER to the conventional scheme for massive MIMO systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.21-29
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• 2014

Due to enormous number of user and limited memory space, the memory saving is become an important issue for big data service these days. In the large scaled multiple-input multiple-output (MIMO) system, the Teoplitz channel can play the significance rule to improve the performance as well as power efficiency. In this paper, we propose a Toeplitz channel decomposition based on matrix vectorization. Here we use Toeplitz matrix to the channel for large scaled MIMO system. And we show that the Toeplitz Jacket matrices are decomposed to Cooley-Tukey sparse matrices like fast Fourier transform (FFT).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.32-35
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• 2018

Massive multiple-input multiple-output (MIMO) transmission is an essential technique for achieving the high bandwidth efficiency required in 5G mobile communication systems. Various forms of arrays can be used as the number of antenna elements increases for massive MIMO transmission. In this letter, we propose a beamforming algorithm applicable to multiuser MIMO transmission using uniform circular arrays. By employing quasi-orthogonal beam pairs obtained from the inter-beam correlation information, we minimize inter-user interference and evaluate the resulting performance gain.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.58-64
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• 2016

This paper proposes the efficient transmit antenna selection (TAS) scheme considering trade-off between the performance and the complexity in massive MIMO system. The massive MIMO system is a core technology to achieve performance objectives for 5 generation wireless communication. It achieve high spectral efficiency, a reliability, and a diversity gain. However many RF chains required by massive transmit antennas equipped in a base station create the problem such as high hardware cost and complexity. Therefor we investigates the transmit antenna selection scheme, in which the number of RF chains of BS is reduced, and the trade-off between the performance and the complexity is considered for proposed scheme. And, the spectral efficiency and complexity are analysed by transmit antenna selection schemes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.119-125
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• 2015

In this paper, we introduce a Hadamard matrix interstream transmission based blind channel estimation for multi-cells multiple-input and multiple-output (MIMO) networks. The proposed scheme is based on a network with mobile stations (MS) which are deployed with multi cells. We assume that the MS have the signals from both cells. The signal from near cell are considered as desired signal and the signals from the other cells are interference signal. Since the channel is blind, so that we transmit Hadamard matrix pattern pilot stream to estimate the channel; that gives easier and fast channel estimation for large scale MIMO channel. The computation of Hadamard based system takes only complex additions, and thus the complexity of which is much lower than the scheme with Fourier transform since complex multiplications are not needed. The numerical analysis will give perfection of proposed channel estimation.

• Electronics and Telecommunications Trends
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• v.26 no.4
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• pp.165-174
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• 2011

삼성전자와 한국전자통신연구원이 공동으로 기술개발에 성공하여 2006년 6월 국내에서 세계 최초로 서비스를 개시한 WiBro는 최대 전송속도 하향 75Mbps($2{\times}2$ MIMO)/상향 50Mbps($1{\times}n$ MIMO), 시속 250km/h로 이동하면서 사용할 수 있는 기술이다. 2011년 1분기 기준 전세계 90개국 195개 사업자가 WiBro 서비스를 제공 또는 준비 중인데, 최근 대규모 WiBro 사업자인 러시아 Yota와 미국 Clearwire가 LTE로의 전환 가능성을 시사하는 등 글로벌 WiBro 사업에 대한 위기감이 나타나고 있다. 본 고에서는 국내외의 WiBro의 시장 현황 및 전망을 살펴보고, 국내로의 시사점을 모색해보고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.723-731
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• 2016

A core technological base to provide enhanced data rates required by 5G mobile wireless communications is the improved bandwidth efficiency using massive multiple-input multiple-output (MIMO) transmission. MIMO transmission requires the channel estimation using the channel state information reference signaling (CSI-RS) and appropriate beamforming, thus the design of the codebook defining proper beamforming vectors is an important issue. In this paper, we propose a multi-rank codebook based on the discrete Fourier transform (DFT) matrix, by utilizing statistical properties of the channel generated by the spatial channel model (SCM). The proposed method includes a structural change of the precoding matrix indicator (PMI) by considering the phase difference distributions between adjacent antenna elements, as well as the selected codevector characteristics of each transmission layer. Performance gain of the proposed method is evaluated and verified by making the performance comparison to the 3GPP standard codebooks adopted by Long-Term Evolution (LTE) systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1559-1565
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• 2021

In this paper, an antenna selection scheme is proposed in massive multi-user multiple input multiple output (MU-MIMO) systems. The proposed antenna selection scheme can achieve almost the same performance as a conventional scheme while significantly reducing the overhead of feedback by using deep reinforcement learning (DRL). Each user compares the channel gains of massive antennas in base station (BS) to the L-largest channel gain, converts them to one-bit binary numbers, and feed them back to BS. Thus, the feedback overhead can be significantly reduced. In the proposed scheme, DRL is adopted to prevent the performance loss that might be caused by the reduced feedback information. We carried out extensive Monte-Carlo simulations to analyze the performance of the proposed scheme and it was shown that the proposed scheme can achieve almost the same average sum-rates as a conventional scheme that is almost optimal.

• The Transactions of the Korea Information Processing Society
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• v.5 no.7
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• pp.1791-1800
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• 1998

본 논문에서는 Mamdani 방법과 Koczy 방법의 퍼지 추론 알고리즘에 대햇 병렬머신에 적합한 병렬 퍼지 추론 방법을 제안하고, 효율적인 병렬 퍼지 아키텍처를 설계한다. 제안된 아키텍처는 비교적 높은 성능을 갖고, 확장이 용이한 구조로서, 여러개의 FPE(Fuzzy Processing Element), CP(Control Processor), 메모리 모듈, 상호연결망 및 Min 회로로 구성되어 있다. 이러한 구조의 특징은 iqjsWo의 FPE는 I번째의 전건부 및 I번째의 후건부의 처리만을 수행하기 때문에 전건부, 변수들의 처리는 각각 병렬도 수행되고, 후건부의 처리도 또한 각각 병렬로 수행된다. 따라서 프로세서의 활용도가 높아지며, 전건부와 후건부의 변수, 퍼지규칙의수에 관계없이 쉽게 구성할 수 있다. 이러한 구조는 실시간에 고속추론을 요하는 시스템 또는 전건부와 후건부의 변수가 많은 대규모 전문가 시스템에 사용되어 질 수 있으며, MISO(Multiple-input, Single-output) 시스템보다 MIMO(Multiple-input, Multiple-output) 시스템에 특히 적합하다.