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Group-Sparse Channel Estimation using Bayesian Matching Pursuit for OFDM Systems
( Yi Liu ),( Wenbo Mei ),( Huiqian Du ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.2
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.
Yuanhong Zhong,Yao Zhou,Qilun Lei 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.9
It is widely accepted that SC-FDE (Single-Carrier Frequency Domain Equalization) is an excellent candidate for broadband wireless systems. Channel estimation is one of the key challenges in SC-FDE, since accurate channel estimation can significantly improve the equalization at the receiver and consequently enhance the communication performances. In this paper, we proposed a simple sparse channel estimation method for SC-FDE system based on noise space, through sorting the results of the Least-squares (LS) channel estimation, channel tap locations and value are evaluated. The proposed system can realize channel estimation at a very low complexity, and simulation result shows that it can achieve significantly improved performance in frequency selective fading sparse channel.
Non-stationary Sparse Fading Channel Estimation for Next Generation Mobile Systems
( Saadat Dehgan ),( Changiz Ghobadi ),( Javad Nourinia ),( Jie Yang ),( Guan Gui ),( Ehsan Mostafapour ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.3
In this paper the problem of massive multiple input multiple output (MIMO) channel estimation with sparsity aware adaptive algorithms for 5<sup>th</sup> 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.
고속페이딩 채널 극복을 위한 ATSC DTV용 스파스 적응 등화기
허노익(No-Ik Heo),오해석(Hae-Sock Oh),한동석(Dong Seog Han) 한국방송·미디어공학회 2005 방송공학회논문지 Vol.10 No.1
An equalization algorithm is proposed to guarantee a stable performance in fast fading channels for digital television (DTV) systems from the advanced television system committee (ATSC) standard. In channels with high Doppler shifts. the conventional equalization algorithm shows severe performance degradation. Although the conventional equalizer compensates poor channel conditions to some degree. long filter taps required to overcome long delay profiles are not suitable for fast fading channels. The proposed sparse equalization algorithm is robust to the multi paths with long delay profiles as well as fast fading by utilizing channel estimation and equalizer initialization. It can compensate fast fading channels with high Doppler shifts using a filter tap selection technique as well as variable step-sizes. Under the ATSC test channels. the proposed algorithm is analyzed and compared with the conventional equalizer. Although the proposed algorithm uses small number of filter taps compared to the conventional equalizer. it is stable and has the advantages of fast convergence and channel tracking.
Minhyun Kim,Lee, Yong H. IEEE 2015 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY Vol.64 No.6
<P>We consider the design of a hybrid multiple-input multiple-output (MIMO) processor consisting of a radio frequency (RF) beamformer and a baseband MIMO processor for millimeter-wave communications over multiuser interference channels. Sparse approximation problems are formulated to design hybrid MIMO processors approximating the minimum-mean-square-error transmit/receive processors in MIMO interference channels. They are solved by orthogonal-matching-pursuit-based algorithms that successively select RF beamforming vectors from a set of candidate vectors and optimize the corresponding baseband processor in the least squares sense. It is shown that various beamformers can be designed by considering different types of candidate vector sets. Simulation results demonstrate the advantage of the proposed design over the conventional method that designs the baseband processor after steering the RF beams.</P>
Sparse Channel Estimation in OFDM Systems via Improved Tap Detection
Xiaolin Shi,Yixin Yang,Long Yang 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.10
Many wireless channels encountered in practice tend to exhibit the structure of sparse multipath due to large bandwidth or large number of antennas. High-rate data wireless communications over multipath wireless channels usually require that the channel response be known at the receiver. In this paper, a novel scheme for the estimation of sparse wireless channels is developed. The initial estimation of the channel taps is obtained by the unstructured least-squares (LS) method. Then, the presence of a channel tap is detected via an improved threshold obtained by applying the nature of sparse channels and the statistics of the noise vector. At last, the channel estimate is refined by deploying the knowledge previously acquired on the position of the nonzero taps and the structured LS method. The proposed method is compared and contrasted with the existing sparse estimation methods. And the results show the validity of the proposed method.
( Chen Wang ),( Yong Fang ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.10
In this paper, we study the sparse signal recovery that uses information of both support and amplitude of the sparse signal. A convergent iterative algorithm for sparse signal recovery is developed using Majorization-Minimization-based Non-convex Optimization (MM-NcO). Furthermore, it is shown that, typically, the sparse signals that are recovered using the proposed iterative algorithm are not globally optimal and the performance of the iterative algorithm depends on the initial point. Therefore, a modified MM-NcO-based iterative algorithm is developed that uses prior information of both support and amplitude of the sparse signal to enhance recovery performance. Finally, the modified MM-NcO-based iterative algorithm is used to estimate the time-varying sparse wireless channels with temporal correlation. The numerical results show that the new algorithm performs better than related algorithms.
( Yuan Hong Zhong ),( Zhi Yong Huang ),( Bin Zhu ),( Hua Wu ) 한국정보처리학회 2015 Journal of information processing systems Vol.11 No.3
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.
Zhong, Yuan-Hong,Huang, Zhi-Yong,Zhu, Bin,Wu, Hua Korea Information Processing Society 2015 Journal of information processing systems Vol.11 No.3
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.