• 한국위성정보통신학회논문지
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• 제7권1호
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• pp.53-58
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• 2012

본 논문에서는 sparse 채널에서 대표적인 채널 추정 기법들의 오차 성능을 비교 및 분석한다. 오차 성능을 비교하기 위해 크라머-라오 경계를 이용하여 최소평균자승오차 추정기법의 하한 경계를 구하고 이를 정합 추적 기법의 상한 경계와 분석한다. 분석 결과로부터 추정 탭 개수와 신호 대 잡음비에 따라 기존에 sparse 채널에서 효율적인 추정기법으로 알려진 정합 추적 기법보다 최소평균 자승오차 추정기법의 오차가 적을 수 있음을 보인다. 레일리이 페이딩 분포를 갖는 두 개의 sparse 채널에 대한 전산모의실험 결과 신호 대 잡음비에 따라 두 추정 기법의 오차 성능이 반전되는 경우를 보였다.

• Journal of Information Processing Systems
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• 제11권3호
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• pp.342-353
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• 2015

It is widely accepted that single carrier frequency division multiple access (SC-FDMA) is an excellent candidate for broadband wireless systems. Channel estimation is one of the key challenges in SC-FDMA, since accurate channel estimation can significantly improve equalization at the receiver and, consequently, enhance the communication performances. In this paper, we study the application of compressive sensing for sparse channel estimation in a SC-FDMA system. By skillfully designing pilots, their patterns, and taking advantages of the sparsity of the channel impulse response, the proposed system realizes channel estimation at a low cost. Simulation results show that it can achieve significantly improved performance in a frequency selective fading sparse channel with fewer pilots.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권2호
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• pp.583-599
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• 2015

We apply the Bayesian matching pursuit (BMP) algorithm to the estimation of time-frequency selective channels in orthogonal frequency division multiplexing (OFDM) systems. By exploiting prior statistics and sparse characteristics of propagation channels, the Bayesian method provides a more accurate and efficient detection of the channel status information (CSI) than do conventional sparse channel estimation methods that are based on compressive sensing (CS) technologies. Using a reasonable approximation of the system model and a skillfully designed pilot arrangement, the proposed estimation scheme is able to address the Doppler-induced inter-carrier interference (ICI) with a relatively low complexity. Moreover, to further reduce the computational cost of the channel estimation, we make some modifications to the BMP algorithm. The modified algorithm can make good use of the group-sparse structure of doubly selective channels and thus reconstruct the CSI more efficiently than does the original BMP algorithm, which treats the sparse signals in the conventional manner and ignores the specific structure of their sparsity patterns. Numerical results demonstrate that the proposed Bayesian estimation has a good performance over rapidly time-varying channels.

• 전기전자학회논문지
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• 제16권3호
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• pp.258-264
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• 2012

주파수 선택적 페이딩 채널을 위한 선형 채널 추정 방식의 성능은 파일럿의 개수에 비례하므로 채널 추정의 정확도를 높이기 위해서 많은 파일럿을 쓰지 않을 수 없으며 필연적으로 전송 효율성이 낮아지는 단점이 있다. 또한 다중경로 채널의 희소(sparse)한 특성을 활용하지 않고 있다. 본 논문에서는 압축센싱 기법을 이용하여 아주 적은 수의 파일럿으로 희소한 채널을 추정하는 정합추구 기반 알고리듬과 간섭도(coherence)를 최소화하기 위한 파일럿 배치 방법을 제안한다. 또한 모의 실험을 통해 LS (least square) 채널 추정 방식보다 적은 수의 파일럿으로 우수한 채널 추정 성능을 보임을 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1047-1062
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• 2018

In this paper the problem of massive multiple input multiple output (MIMO) channel estimation with sparsity aware adaptive algorithms for $5^{th}$ generation mobile systems is investigated. These channels are shown to be non-stationary along with being sparse. Non-stationarity is a feature that implies channel taps change with time. Up until now most of the adaptive algorithms that have been presented for channel estimation, have only considered sparsity and very few of them have been tested in non-stationary conditions. Therefore we investigate the performance of several newly proposed sparsity aware algorithms in these conditions and finally propose an enhanced version of RZA-LMS/F algorithm with variable threshold namely VT-RZA-LMS/F. The results show that this algorithm has better performance than all other algorithms for the next generation channel estimation problems, especially when the non-stationarity gets high. Overall, in this paper for the first time, we estimate a non-stationary Rayleigh fading channel with sparsity aware algorithms and show that by increasing non-stationarity, the estimation performance declines.

• 한국정보통신학회논문지
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• 제18권5호
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• pp.1061-1066
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• 2014

천해에서 음파 전달은 매우 복잡하며, sparse한 전달 특성을 갖는다. 이러한 환경에서 수중음향통신 시스템의 성능을 향상시키기 위하여 채널을 추정하기 위한 여러 방법들이 연구되었다. 본 논문에서는 기존의 sparse-aware LMS(Least Mean Square) 알고리즘들보다 빠른 수렴속도를 갖는 LMS 기반 채널 추정 알고리즘을 제안하였다. 제안한 방법은 $L_p$-norm LMS 알고리즘과 soft decision 과정을 결합한 것이다. 모의실험은 실제 해상 실험을 통하여 얻은 수중 음속 데이터를 바탕으로 수행되었다. 그 결과 제안한 방법이 기존의 방법들보다 빠른 수렴속도와 향상된 성능을 보이는 것을 확인하였다.

• 말소리와 음성과학
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• 제5권4호
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• pp.227-232
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• 2013

Since a reverberation filter is generally much shorter than the corresponding dereverberation filter, a single-channel speech dereverberation method based on reverberation filter estimation has been developed to improve its performance. Unfortunately, a typical reverberation filter still requires too many coefficients to be accurately estimated using limited speech observations. In order to exploit sparseness of reverberation filter coefficients, in this paper, we present an algorithm to impose a sparse prior to the process of reverberation filter estimation. Simulation results demonstrate that the sparse prior imposition further improves performance of the speech dereverberation method based on reverberation filter estimation.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1083-1096
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• 2021

Compressed sensing-based matching pursuit algorithms can estimate the sparse channel of massive multiple input multiple-output systems with short pilot sequences. Although they have the advantages of low computational complexity and low pilot overhead, their accuracy remains insufficient. Simply multiplying the weight value and the estimated channel obtained in different iterations can only improve the accuracy of channel estimation under conditions of low signal-to-noise ratio (SNR), whereas it degrades accuracy under conditions of high SNR. To address this issue, an improved weighted matching pursuit algorithm is proposed, which obtains a suitable weight value u_op by training the channel data. The step of the weight value increasing with successive iterations is calculated according to the sparsity of the channel and u_op. Adjusting the weight value adaptively over the iterations can further improve the accuracy of estimation. The results of simulations conducted to evaluate the proposed algorithm show that it exhibits improved performance in terms of accuracy compared to previous methods under conditions of both high and low SNR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.2102-2123
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• 2016

This paper considers a channel estimation scheme for millimeter-wave multiuser multiple-input multiple-output systems. According to the proposed method, parts of the beams are selected and the channel parameters are estimated according to the sparsity of channels and the orthogonality of the beams. Since the beams for each channel become distinct and the signal power increases with the increased number of antennas, the proposed approach is able to achieve good estimation performance. As a result, the sum rate can be increased in comparison with traditional approaches, and channels can be estimated with fewer pilot symbols. Numerical results verify that the proposed approach outperforms traditional approaches in cases with large numbers of antennas.

• 방송공학회논문지
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• 제10권2호
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• pp.166-173
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• 2005

본 논문에서는 직교 주파수 분할 다중 접속 (orthogonal frequency division multiplexing, OFDM) 시스템에서 MP (matching pursuit) 알고리듬을 이용하는 이동 채널 추정법을 제안한다. OFDM 시스템에서 기존의 채널추정 알고리듬으로 쓰이는 LS (least square) 알고리듬은 잡음의 영향으로 채널 추정 오류의 가능성을 가지고 있다. 본 논문에서는 MP 알고리듬을 이용하여 스파스(sparse)형태의 채널을 추정함으로써 다중경로 신호가 없다고 가정되는 시간 구간에서 발생될 수 있는 잡음에 의한 영향을 줄인다. 그리고 연속으로 전송되는 파일럿 정보를 이용하여 변화하는 채널을 추정한다. 64QAM,그리고 이동 다중 경로 페이딩 채널에 대해서 심볼 오율을 측정하여 제안된 알고리듬과 LS알고리듬의 성능을 비교한다.