Analysis Of Sparse Channel Estimation

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Analysis of Sparse Channel Estimation

Author : Brian Michael Carroll
Publisher :
ISBN 13 :
Total Pages : 98 pages
Book Rating : 4.:/5 (587 download)

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Book Synopsis Analysis of Sparse Channel Estimation by : Brian Michael Carroll

Download or read book Analysis of Sparse Channel Estimation written by Brian Michael Carroll and published by . This book was released on 2009 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Channel Estimation is an essential component in applications such as radar and data communication. In multi path time varying environments, it is necessary to estimate time-shifts, scale-shifts (the wideband equivalent of Doppler-shifts), and the gains/phases of each of the multiple paths. With recent advances in sparse estimation (or ``compressive sensing"), new estimation techniques have emerged which yield more accurate estimates of these channel parameters than traditional strategies. These estimation strategies, however, restrict potential estimates of time-shifts and scale-shifts to a finite set of values separated by a choice of grid spacing. A small grid spacing increases the number of potential estimates, thus lowering the quantization error, but also increases complexity and estimation time. Conversely, a large grid spacing lowers the number of potential estimates, thus lowering the complexity and estimation time, but increases the quantization error. In this thesis, we derive an expression which relates the choice of grid spacing to the mean-squared quantization error. Furthermore, we consider the case when scale-shifts are approximated by Doppler-shifts, and derive a similar expression relating the choice of the grid spacing and the quantization error. Using insights gained from these expressions, we further explore the effects of the choice and grid spacing, and examine when a wideband model can be well approximated by a narrowband model.

A Study of Blind Sparse Channel Estimation Based on Compressed Sensing for Massive MIMO Systems with Spatial Modulation

Author : Han-Wen Tsai
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (15 download)

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Book Synopsis A Study of Blind Sparse Channel Estimation Based on Compressed Sensing for Massive MIMO Systems with Spatial Modulation by : Han-Wen Tsai

Download or read book A Study of Blind Sparse Channel Estimation Based on Compressed Sensing for Massive MIMO Systems with Spatial Modulation written by Han-Wen Tsai and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

EFFECTIVE SPARSE CHANNEL ESTIMATION TECHNIQUE FOR MIMO-OFDM SYSTEM

Author : Dr.Maddala Vijayalakshmi
Publisher : Archers & Elevators Publishing House
ISBN 13 : 8119385969
Total Pages : 58 pages
Book Rating : 4.1/5 (193 download)

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Book Synopsis EFFECTIVE SPARSE CHANNEL ESTIMATION TECHNIQUE FOR MIMO-OFDM SYSTEM by : Dr.Maddala Vijayalakshmi

Download or read book EFFECTIVE SPARSE CHANNEL ESTIMATION TECHNIQUE FOR MIMO-OFDM SYSTEM written by Dr.Maddala Vijayalakshmi and published by Archers & Elevators Publishing House. This book was released on with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Study of Basis Reduction-based Pilot Allocation for Sparse Channel Estimation in OFDM Systems

Author : 劉旭清
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (1 download)

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Book Synopsis A Study of Basis Reduction-based Pilot Allocation for Sparse Channel Estimation in OFDM Systems by : 劉旭清

Download or read book A Study of Basis Reduction-based Pilot Allocation for Sparse Channel Estimation in OFDM Systems written by 劉旭清 and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Efficient Sparse Channel Estimation for High-Mobility OFDM Systems

Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (141 download)

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Book Synopsis Efficient Sparse Channel Estimation for High-Mobility OFDM Systems by :

Download or read book Efficient Sparse Channel Estimation for High-Mobility OFDM Systems written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Sparse Adaptive Filtering Techniques for Channel Estimation

Author : Muhammad Lawan Aliyu
Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783659468759
Total Pages : 76 pages
Book Rating : 4.4/5 (687 download)

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Book Synopsis Sparse Adaptive Filtering Techniques for Channel Estimation by : Muhammad Lawan Aliyu

Download or read book Sparse Adaptive Filtering Techniques for Channel Estimation written by Muhammad Lawan Aliyu and published by LAP Lambert Academic Publishing. This book was released on 2015-06-17 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, sparse signal approximation has become an increasingly important research area in signal processing. It attracts a lot of interest due to its wide range of practical applications. In this work, a novel adaptive filtering algorithm with relative low computational complexity that is capable of exploiting the sparsity of systems is proposed. The basic idea here is, we adopt a p-norm constraint in the cost function of the variable step-size least mean square (VSSLMS) algorithm. This constrain imposes a zero attraction at each filter coefficient based on their respective relative value. Also, the convergence analysis of the proposed algorithm is presented and the stability condition is derived. The performance of the proposed algorithm has been compared to those of the Zero Attraction Least Mean Square(ZA-LMS), windowing ZA-LMS(wZA-LMS), Non-uniform Norm Constraint LMS(NNCLMS) in a system identification setting for different additive Gaussian noise(AGN), additive correlated noise(ACN)and additive impulsive noise(AIN) environments. The proposed algorithm has always shown superior performance to the others with less or comparable number of computations

Sparse Channel Estimation Based on Compressed Sensing Theory for UWB Systems

Author : Eva Lagunas Targarona
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (85 download)

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Book Synopsis Sparse Channel Estimation Based on Compressed Sensing Theory for UWB Systems by : Eva Lagunas Targarona

Download or read book Sparse Channel Estimation Based on Compressed Sensing Theory for UWB Systems written by Eva Lagunas Targarona and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Sparse Channel Estimation and Tracking for Underwater Acoustic Communications

Author : Danqing Yin
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Book Synopsis Sparse Channel Estimation and Tracking for Underwater Acoustic Communications by : Danqing Yin

Download or read book Sparse Channel Estimation and Tracking for Underwater Acoustic Communications written by Danqing Yin and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on estimation and tracking of underwater acoustic channels. A model of underwater acoustic channel suitable to study the channel estimation problem is constructed. The model is used together with a Bellhop acoustic wave propagation simulator to generate channels for various propagation environments, depths and distances, and we studied their sparseness and variation properties. Finally a number of estimation methods such as basis pursuit and approximate message passing are adapted to channel estimation problems and tested on a number of channels. Window-based and Kalman- filter based channel tracking is also studied. A detailed comparison of estimation and tracking methods is presented.

Efficiently Estimating a Sparse Delay-doppler Channel

Author : Alisha Zachariah
Publisher :
ISBN 13 :
Total Pages : 90 pages
Book Rating : 4.:/5 (119 download)

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Book Synopsis Efficiently Estimating a Sparse Delay-doppler Channel by : Alisha Zachariah

Download or read book Efficiently Estimating a Sparse Delay-doppler Channel written by Alisha Zachariah and published by . This book was released on 2020 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple wireless sensing tasks, e.g., radar detection for driver safety, involve estimating the "channel" or relationship between signal transmitted and received. In this paper, we focus on a certain channel model known as the delay-doppler channel. This model begins to be useful in the high frequency carrier setting, which is increasingly common with developments in millimeter-wave technology. Moreover, the delay-doppler model then continues to be applicable even when using signals of large bandwidth, which is a standard approach to achieving high resolution channel estimation. However, when high resolution is desirable, the standard approach results in a tension with the desire for efficiency because, in particular, it immediately implies that the signals in play live in a space of very high dimension N (e.g., ~10^6 in some applications), as per the Shannon-Nyquist sampling theorem. To address this difficulty, in this paper we propose a novel randomized estimation scheme called Sparse Channel Estimation, or SCE for short, for channel estimation in the k-sparse setting (e.g., k objects in radar detection). This scheme involves an estimation procedure with sampling and space complexity both on the order of k(log N)^3, and arithmetic complexity on the order of k(log N)^3+k^2, for N sufficiently large. To the best of our knowledge, Sparse Channel Estimation (SCE) is the first of its kind to achieve these complexities simultaneously -- it seems to be extremely efficient! As an added advantage, it is a simple combination of three ingredients, two of which are well-known and widely used, namely digital chirp signals and discrete Gaussian filter functions, and the third being recent developments in sparse fast fourier transform algorithms. We note that the design of Sparse Channel Estimation(SCE) is based on a digital channel model which presumes the so-called "on-the-grid" assumption. This assumption is made in a heuristic manner -- while SCE can still be used in the off-the-grid setting, proving guarantees in this more general setting remains to be future work.

Compressed Sensing-based Channel Estimation and Prediction for Underwater Acoustic Communications

Author : Yi Zhang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (131 download)

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Book Synopsis Compressed Sensing-based Channel Estimation and Prediction for Underwater Acoustic Communications by : Yi Zhang

Download or read book Compressed Sensing-based Channel Estimation and Prediction for Underwater Acoustic Communications written by Yi Zhang and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis develops approaches for estimating and predicting sparse shallow-water acoustic communication channels. The broadband shallow-water channel has three characterizations: a large dimension of channel impulse response caused by excessively long delay spread, fast temporal variability induced by scattering from the moving sea surface, and a sparse channel structure due to the resolvable paths. Traditional least square estimation techniques fail to utilize the sparse channel structure, and suffer from the limitations on the capability of estimating large-dimensional channels with rapid fluctuations. Compressed sensing also known as compressive sensing (CS), has been intensively studied recently. It has been applied in various areas such as imaging, radar, speech recognition, and data acquisition. Recently, applying CS to sparse channel estimation has been largely accepted. This thesis details the application of CS to sparse estimation of both time-invariant and time-varying shallow-water acoustic channels. Specifically, various reconstruction algorithms are used to find the sparse channel coefficients. However, a priori knowledge of channel sparsity is often not available in practice. The first part of the thesis proposes an improved greedy pursuit algorithm which iteratively identifies the sparse channel coefficients without requiring a priori knowledge of channel sparsity. Then, the proposed algorithm is employed to estimate both time-invariant and time-varying sparse channels. In addition, a comparative study of the state-of-the-art of various CS-based signal reconstruction algorithms is performed to gain better understanding of the mathematical insights. Furthermore, based on CS theory, different pilot placement choices will directly affect the performance of the channel estimation algorithm. The second part of the thesis investigates the pilot pattern design in sparse channel estimation. Unlike the equally spaced pilots for conventional channel estimation, randomly placed pilot tones are most used in existing CS-based channel estimation methods. In order to improve the efficiency of the optimal pilot pattern searching, a novel pilot pattern selection scheme is proposed based on the concatenated cyclic difference set. The performance of the proposed design is also compared with the existing search-based pilot placement methods. It should be noted that the proposed reconstruction algorithm and the pilot placement scheme are not restricted to underwater acoustic communication systems, but they can be applied so sparse channel estimation in other communication systems. Finally, an outdated channel estimation will lead to severe performance degradation when the channel varies rapidly. Hence, to predict future channel state information, an efficient sparse channel prediction scheme is proposed which does not require any statistical a priori knowledge of channels and noise. A receiver structure which combines a sparse channel estimator and a decision feedback based adaptive channel predictor is developed to further improve the prediction accuracy.Simulation results are shown to demonstrate the performance of the proposed algorithms and schemes. The study of this thesis contributes to a better understanding of the channel physical constraints on algorithm design and potential performance improvement.

Compressive Sensing

Author : Dinesh Nandakumar Shenoy
Publisher :
ISBN 13 : 9780355863505
Total Pages : 35 pages
Book Rating : 4.8/5 (635 download)

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Book Synopsis Compressive Sensing by : Dinesh Nandakumar Shenoy

Download or read book Compressive Sensing written by Dinesh Nandakumar Shenoy and published by . This book was released on 2018 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulation results show that the BER results for a system based on Sparse estimation of the channel are much better than a system with Least Square Estimation at high signal to noise ratios (SNR).

Analysis of Second Order Statistics for Improved Channel Estimation in Wireless Communications

Author : Ingo Viering
Publisher :
ISBN 13 : 9783183733101
Total Pages : 101 pages
Book Rating : 4.7/5 (331 download)

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Book Synopsis Analysis of Second Order Statistics for Improved Channel Estimation in Wireless Communications by : Ingo Viering

Download or read book Analysis of Second Order Statistics for Improved Channel Estimation in Wireless Communications written by Ingo Viering and published by . This book was released on 2003 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Adaptive Algorithms for Wireless Channel Estimation

Author : Tareq Y. Al-Naffouri
Publisher :
ISBN 13 :
Total Pages : 294 pages
Book Rating : 4.:/5 (794 download)

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Book Synopsis Adaptive Algorithms for Wireless Channel Estimation by : Tareq Y. Al-Naffouri

Download or read book Adaptive Algorithms for Wireless Channel Estimation written by Tareq Y. Al-Naffouri and published by . This book was released on 2005 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Latent Variable Analysis and Signal Separation

Author : Emmanuel Vincent
Publisher : Springer
ISBN 13 : 3319224824
Total Pages : 534 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Latent Variable Analysis and Signal Separation by : Emmanuel Vincent

Download or read book Latent Variable Analysis and Signal Separation written by Emmanuel Vincent and published by Springer. This book was released on 2015-08-14 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented – 29 accepted as oral presentations and 32 accepted as poster presentations – were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear blind source separation; sparse and low rank modeling for acoustic signal processing.

Signal-perturbation-free Semi-blind Channel Estimation for MIMO-OFDM Systems

Author : Feng Wan
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (462 download)

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Book Synopsis Signal-perturbation-free Semi-blind Channel Estimation for MIMO-OFDM Systems by : Feng Wan

Download or read book Signal-perturbation-free Semi-blind Channel Estimation for MIMO-OFDM Systems written by Feng Wan and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) has been considered as a strong candidate for the beyond 3G (B3G) wireless communication systems, due to its high data-rate wireless transmission performance. It is well known that the advantages promised by MIMO-OFDM systems rely on the precise knowledge of the channel state information (CSI). In real wireless environments, however, the channel condition is unknown. Therefore, channel estimation is of crucial importance in MIMO-OFDM systems. Semi-blind channel estimation as a combination of the training-based or pilot-assisted method and the pure blind approach is considered to be a feasible solution for practical wireless systems due to its better estimation accuracy as well as spectral efficiency. In this thesis, we address the semi-blind channel estimation issue of MIMO-OFDM systems with an objective to develop very efficient channel estimation approaches. In the first part of the dissertation, several nulling-based semi-blind approaches are presented for the estimation of time-domain MIMO-OFDM channels. By incorporating a blind constraint that is derived from MIMO linear prediction (LP) into a training-based least-square method, a semi-blind solution for the time-domain channel estimation is first obtained. It is revealed through a perturbation analysis that the semi-blind solution is not subject to signal perturbation and therefore is superior to pure blind estimation methods. The LP-based semi-blind method is then extended for the channel estimation of MIMO-OFDM systems with pulse-shaping. By exploiting the pulse-shaping filter in the transmitter and the matched filter in the receiver, a very efficient semi-blind approach is developed for the estimation of sampling duration based multipath channels. A frequency-domain correlation matrix estimation algorithm is also presented to facilitate the computation of time-domain second-order statistics required in the LP-based method. The nulling-based semi-blind estimation issue of sparse MIMO-OFDM channels is also addressed. By disclosing and using a relationship between the positions of the most significant taps (MST) of the sparse channel and the lags of nonzero correlation matrices of the received signal, a novel estimation approach consisting of the MST detection and the sparse channel estimation, both in a semi-blind fashion, is developed. An intensive simulation study of all the proposed nulling-based methods with comparison to some existing techniques is conducted, showing a significant superiority of the new methodologies. The second part of the dissertation is dedicated to the development of two signal-perturbation-free (SPF) semi-blind channel estimation algorithms based on a novel transmit scheme that bears partial information of the second-order statistics of the transmitted signal to receiver. It is proved that the new transmit scheme can completely cancel the signal perturbation error in the noise-free case, thereby improving largely the estimation accuracy of correlation matrix for channel estimation in noisy conditions. It is also shown that the overhead caused by the transmission of the 8PF data is negligible as compared to that of regular pilot signals. By using the proposed transmit scheme, a whitening rotation (WR)-based algorithm is first developed for frequency-domain MIMO-OFDM channel estimation. It is shown through both theoretical analysis and simulation study that the new WR-based algorithm significantly outperforms the conventional WR-based method and the nulling-based semi-blind method. By using MIMO linear prediction, the new WR-based algorithm utilizing the 8PF transmit scheme is then extended for time-domain MIMO-OFDM channel estimation. Computer simulations show that the proposed signal-perturbation-free LP-based semi-blind solution performs much better than the LP semi-blind method without using the proposed transmit scheme, the LS method as well as the nulling-based semi-blind method in terms of the MSE of the channel estimate.

Modelling, Simulation and Data Analysis in Acoustical Problems

Author : Claudio Guarnaccia
Publisher : MDPI
ISBN 13 : 3039282840
Total Pages : 584 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Modelling, Simulation and Data Analysis in Acoustical Problems by : Claudio Guarnaccia

Download or read book Modelling, Simulation and Data Analysis in Acoustical Problems written by Claudio Guarnaccia and published by MDPI. This book was released on 2020-06-23 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years.

Latent Variable Analysis and Signal Separation

Author : Vincent Vigneron
Publisher : Springer Science & Business Media
ISBN 13 : 364215994X
Total Pages : 672 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Latent Variable Analysis and Signal Separation by : Vincent Vigneron

Download or read book Latent Variable Analysis and Signal Separation written by Vincent Vigneron and published by Springer Science & Business Media. This book was released on 2010-09-27 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thisvolumecollectsthepaperspresentedatthe9thInternationalConferenceon Latent Variable Analysis and Signal Separation,LVA/ICA 2010. The conference was organized by INRIA, the French National Institute for Computer Science and Control,and was held in Saint-Malo, France, September 27–30,2010,at the Palais du Grand Large. Tenyearsafterthe?rstworkshoponIndependent Component Analysis(ICA) in Aussois, France, the series of ICA conferences has shown the liveliness of the community of theoreticians and practitioners working in this ?eld. While ICA and blind signal separation have become mainstream topics, new approaches have emerged to solve problems involving signal mixtures or various other types of latent variables: semi-blind models, matrix factorization using sparse com- nent analysis, non-negative matrix factorization, probabilistic latent semantic indexing, tensor decompositions, independent vector analysis, independent s- space analysis, and so on. To re?ect this evolution towards more general latent variable analysis problems in signal processing, the ICA International Steering Committee decided to rename the 9th instance of the conference LVA/ICA. From more than a hundred submitted papers, 25 were accepted as oral p- sentationsand53 asposter presentations. Thecontent ofthis volumefollowsthe conference schedule, resulting in 14 chapters. The papers collected in this v- ume demonstrate that the research activity in the ?eld continues to range from abstract concepts to the most concrete and applicable questions and consid- ations. Speech and audio, as well as biomedical applications, continue to carry the mass of the applications considered.