• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.17-23
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• 2012

Recently, for spectral efficiency and power saving, an incremental best relay selection of a cooperative diversity scheme is proposed. However during the best relay selection process, there may exist a delay between channel estimation and actual data transmission. Consequently, this delay causes outdated channel state information (CSI). We analytically derive the effect of the outdated CSI to an incremental best relay selection diversity scheme. It is noted that the system performance deteriorates with decreasing the value of the correlation coefficient sensitively. When the correlation coefficient reduces from 1 to 0.9, the most performance degradation is denoted. However, the performance degradation is diminished with decreasing the correlation coefficient.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.49-58
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• 2006

In this paper, a curve-fitting channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) system in a time-varying frequency-selective fading channel. The method can greatly improve channel state information (CSI) estimation accuracy by performing smoothing and interpolation through consecutive curve-fitting processes in both time domain and frequency domain. It first evaluates least-squares (LS) estimates using pilot symbols and then the estimates are approximated to a polynomial with proper degree in the LS error sense, starting from one preferred domain in which pilots we densely distributed. Smoothing, interpolation, and prediction are performed subsequently to obtain CSI estimates for data transmission. The channel estimation processes are completed by smoothing and interpolating CSI estimates in the other domain once again using the channel estimates obtained in one domain. The performance of proposed method is influenced heavily on the time variation and frequency selectivity of channel and pilot arrangement. Hence, a proper degree of polynomial and an optimum approximation interval according to various system and channel conditions are required for curve-fitting. From extensive simulation results in various channel environments, we see that the proposed method performs better than the conventional methods including the optimal Wiener filtering method, in terms of the mean square error (MSE) and bit error rate (BER).

• Journal of Communications and Networks
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• v.12 no.6
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• pp.605-615
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• 2010

Intercarrier interference (ICI) in orthogonal frequency division multiplexing (OFDM) systems, which causes substantial performance degradation in time-varying fading channels, is analyzed. An equivalent spreading code formulation is derived based on the analogy of OFDM and code division multiple access (CDMA) systems. Techniques as linear multiuser detection in CDMA systems are applied to suppress the ICI in OFDM systems. The performance of linear detection, measured using multiuser efficiency and asymptotic multiuser efficiency, is analyzed given the assumption of perfect channel state information (CSI), which serves as an upper bound for the performance of practical systems. For systems without CSI, time domain and frequency domain channel estimation based linear detectors are proposed. The performance gains and robustness of a linear minimum mean square error (LMMSE) filter over a traditional filter (TF) and matched filter (MF) in the high signal-to-noise ratio (SNR) regime are demonstrated with numerical simulation results.

• 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.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.26-33
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• 2014

For wireless communication systems of (and beyond) LTE-Advanced, multiple-input multiple-output (MIMO) with an increased number of antennas will be utilized for system throughput improvement. When using such an increased number of antenna, an excessive amount of overhead in channel state information (CSI) feedback can be a serious problem. In this paper, we propose methods which reduce the CSI feedback overhead, particularly including application strategies for multi-rank transmission targeted for two or more reception antennas. To reduce the information which is instantaneously transmitted from the reception node to the transmission node, we present a beamforming method utilizing singular value decomposition (SVD) based on channel estimation of partitioned antenna arrays. Since the SVDs for partial matrices of the channel may lose the characteristics of the original unpartitioned matrix, we explain an appropriate scheme to cope with this problem.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.6-12
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• 2011

The fast growing of the number of users requires the development of reliable communication systems able to provide higher data rates. In order to meet those requirements, techniques such as Multiple Input Multiple Out (MIMO) and Orthogonal Frequency Division multiplexing (OFDM) have been developed in the recent years. In order to combine the benefits of both techniques, the research activity is currently focused on MIMO-OFDM systems. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions; and using sub-carrier frequency, and power allocation techniques. Depending on how accurate the feedback-based system obtain the channel state information (CSI) and feed it back to the transmitter without delay, the overall system performance would be poor or optimal. In this paper, we propose a Signal to Noise Ratio (SNR) estimation algorithm where the preamble is known for both sides of the transciever. Through simulations made over several channel environments, we prove that our proposed SNR estimation algorithm is more accurate compared with the traditional SNR estimation.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.506-513
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• 2003

Most existing space-time coding (STC) schemes have been developed for flat fading channels. To obtain antenna diversity gain, they rely on channel state information (CSI) required at the receiver through channel estimation techniques. This paper proposes a new decision feedback decoding scheme for Alamouti-based space-time block coding (STBC) transmission over time-selective fading channels. In wireless channels, time-selective fading effects arise mainly due to Doppler shift and carrier frequency offset, Modelling the time-selective fading channels as the first-order Gauss-Markov processes, we use recursive algorithms such as Kalman filtering, LMS and RLS algorithms for channel tracking. The proposed scheme consists of the symbol decoding stage and channel tracking algorithms. Computer simulations confirm that the proposed scheme shows the better performance and robustness to time-selectivity.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.32-39
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• 2009

When adapting the transmitter to the channel state information(CSI), improved transmission is possible compared to the open loop system where no CSI is provided at the transmitter. However, since the perfect channel information is rarely available at the transmitter, the system design based on the partial CSI becomes an important factor. Especially, in mobile environments, the consideration for the outdated CSI should be applied for mitigating the performance degradation. In this paper, we propose a robust adaptive modulation and coding scheme for bit-interleaved coded orthogonal frequency division multiplexing over time-varying channels. With reasonable feedback overhead, the proposed scheme shows the enhanced performance by compensating for the outdated CSI due to Doppler spread. Simulation results confirm that the performance gain is achieved by applying an accurate BER estimation method.

• Journal of Communications and Networks
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• v.7 no.2
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• pp.157-170
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• 2005

The combination of multiple antennas and multi-carrier code division multiple-access (MC-CDMA) is a strong candidate for the downlink of the next generation mobile communications. The study of such systems in scenarios that model real-life trans-missions is an additional step towards an optimized achievement. We consider a realistic MIMO channel with two or four transmit antennas and up to two receive antennas, and channel state information (CSI) mismatches. Depending on the mobile terminal (MT) class, its number of antennas or complexity allowed, different data-rates are proposed with turbo-coding and asymptotic spectral efficiencies from 1 to 4.5 bit/s/Hz, using three algorithms developed within the European IST-MATRICE project. These algorithms can be classified according to the degree of CSI at base-station (BS): i) Transmit space-frequency prefiltering based on constrained zero-forcing algorithm with complete CSI at BS; ii) transmit beamforming based on spatial correlation matrix estimation from partial CSI at BS; iii) orthogonal space-time block coding based on Alamouti scheme without CSI at BS. All presented schemes require a reasonable complexity at MT, and are compatible with a single-antenna receiver. A choice between these algorithms is proposed in order to significantly improve the performance of MC-CDMA and to cover the different environments considered for the next generation cellular systems. For beyond-3G, we propose prefiltering for indoor and pedestrian microcell environments, beamforming for suburban macrocells including high-speed train, and space-time coding for urban conditions with moderate to high speeds.