• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.860-867
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• 2008

In this paper, we explain differences between SCM and extended SCM(SCME), and investigate how these channel models affects MIMO system level performance. System level simulation is performed according to the number of users and drifting-time intervals with SCM and SCME, respectively. The performance of SCME is slightly better than SCM since mid-paths and the drifting-time in SCME causes more fluctuations in MIMO channels.

• Electronics and Telecommunications Trends
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• v.23 no.3
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• pp.53-60
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• 2008

이동통신 MIMO 채널 모델이란 다중안테나를 사용한 무선 인터페이스 구간 내의 신호처리 모델로서, 무선 통신의 급격한 수요와 이동통신 서비스의 폭발적인 증가로 인해 차세대 이동통신 시스템 개발의 최적화를 위하여 MIMO 시스템 개발의 구현기술 검증에 사용된다. 차세대 이동통신 시스템의 사용 주파수 대역은 2-6GHz 대역으로 예상되며 기존 2G/3G 이동통신 대역폭 보다 큰 10-100MHz의 광대역 무선전송을 목표로 하고 있다. 본 고에서는 이동통신 MIMO 채널 모델링의 개발 및 표준화 동향에 대해서 논의한다. II장에서는 MIMO 채널 모델의 국.내외 개발 동향에 대해서 서술하며, III장에서는 MIMO 채널 모델링을 위한 국제표준화 동향에 대해서 서술한다. 마지막으로 IV장에서 결론을 맺고자 한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1455-1461
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• 2012

MIMO-OFDM which is one of core techniques for the high-speed mobile communication system requires the efficient channel estimation method with low estimation error and computational complexity, for accurately receiving data. In this paper, we propose a channel estimation algorithm with low channel estimation error comparing with LS which is primarily employed to the MIMO-OFDM system, and with low computational complexity comparing with MMSE. The proposed algorithm estimates channel vectors based on the LMS adaptive algorithm in the time domain, and the estimated channel vector is sent to the detector after FFT. We also suggest a preamble architecture for the proposed MIMO-OFDM channel estimation algorithm. The computer simulation example is provided to illustrate the performance of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.45-54
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• 2010

This paper studies the design of a multiuser multiple-input multiple-output (MIMO) system, where a base station (BS) transmits independent messages to multiple users. The remarkable "dirty paper coding (DPC)" result was first presented by Costa that the capacity does not change if the Gaussian interference is known at the transmitter noncausally. While several implementable DPC schemes have been proposed recently for single-user dirty-paper channels, DPC is still difficult to implement directly in practical multiuser MIMO channels. In this paper, we propose a network channel matrix triangulation (NMT) algorithm for utilizing interference known at the transmitter. The NMT algorithm decomposes a multiuser MIMO channel into a set of parallel, single-input single-output dirty-paper subchannels and then successively employs the DPC to each subchannel. This approach allows us to extend practical single-user DPC techniques to multiuser MIMO downlink cases. We present the sum rate analysis for the proposed scheme. Simulation results show that the proposed schemes approach the sum rate capacity of the multiuser MIMO downlink at moderate signal-to-noise ratio (SNR) values.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4A
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• pp.384-389
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• 2004

In this paper, we investigate channel estimation techniques based on the comb-type pilot arrangement for a mobile MIMO OFDM system. Moreover, to enhance channel estimation, an efficient channel estimation technique is proposed. Simulation results show that the proposed channel estimator is accurate and effective for tracking variations of channels between multiple transmit antennas and receive antennas in time-varying radio channels.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.26-33
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• 2008

Signal detection is a key technique in wireless communication system. Recently, several detection algorithms have been developed for multiple-input multiple-output (MIMO) wireless communication systems. However, most research in this area had assumed a flat-fading channel environment and all these techniques are based on the assumption that the channel state information (CSI) at the receiver side is perfect. But in practical situation, the available CSI may be imperfect because of channel estimation errors and/or outdated training. In this paper, we will compare the performance of several detection algorithms in MIMO frequency selective fading channel environment with imperfect CSI.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.8
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• pp.759-764
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• 2004

This paper proposes a method that estimates MIMO channel characteristics analytically using a 3D ray tracing propagation model. We calculate the discrete spatial correlation between sub-channels by considering phase differences of paths, and using this, estimate the mean capacity upper bound of MIMO channel by Jensen's inequality. This analysis model is a deterministic model that do not approach stochastically through measurement nor approach statistically through Monte-Carlo simulations, so this model has high efficiency for time and cost. And based on the electromagnetic theory, this model may analyze quantitatively the parameters which can affect the channel capacity - antenna pattern, polarization mutual coupling, antenna structure and etc. This model may be used for the development of an optimal antenna structure for MIMO systems.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.8
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• pp.748-757
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• 2015

MIMO systems utilizing multiple antenna transmission and reception is one of the key technologies to enhance the capacity of 5G wireless communications. In order to obtain an appropriate performance evaluation of MIMO techniques, the usage of wireless channel model reflecting spatial channel characteristics is required, such as the 3-dimensional spatial channel model(3D SCM) proposed by 3GPP TR36.873 documentation. In this paper, we implement and verify the channel simulation environment based on 3D SCM, to present and compare the characteristics of UMi and UMa environments. We also apply MIMO transmission to the UMa scenario to investigate the channel correlation among antenna elements with different array distances and to identify the corresponding throughput changes. By evaluating the channel power correlations for randomly distributed users within the sector for different horizontal and vertical antenna distances, we present the statistical characteristics which determine the transmission performance under the SCM environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5A
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• pp.475-483
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• 2006

If channel coefficients errors exist in MIMO-OFDM systems, the performance degradation of systems will occurs. In order to improve the performance of MIMO-OFDM systems, the technique of obtaining accurate channel estimation in multipath fading channel is necessary. In this paper, we introduce and propose new channel estimation-modified ICA algorithm. Simulation results shows from BER and SER curves which compare the proposed algorithm under time-varying Rayleigh fading with perfect known channel. The result of channel estimation by the proposed algorithm in this simulation, it shows that PDF(amplitude of channel) are close to the case with perfect known channel at the receiver with respect to uncoded QPSK/16-QAM/64-QAM modulation. Also, we can see that BER and SER curves are very close to the case with perfect known channel. Therefore, we see that the proposed algorithm have a good performance in MIMO-OFDM systems.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.8
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• pp.63-68
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• 2004

The capacity of MIMO systems is numerically analyzed when channel estimation error exists. The analysis shows that the capacity is influenced by Mean Square Error (MSE) as well as average Signal to Noise Ratio (SNR). Furthermore, in this paper we present the standard selecting a channel estimator suitable to a system owing to get a tolerable channel estimation error in a given average SNR and channel capacity loss. The simulation results show that the tolerable MSEs for 1 bps/Hz capacity loss are about 10$^{-2}$ and 10$^{-4}$ at n dB and 40 dB average SNR, respectively.