Robust Channel Estimation for Ultra-wideband Communication Systems Using H [infinity] Algorithm PDF Download

Author: Witty Wong
Publisher:
ISBN:
Category :
Languages : en
Pages : 154

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Author: Xiaofan Yang
Publisher:
ISBN:
Category :
Languages : en
Pages : 94

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In this thesis we consider the design of an ultra-wideband (UWB) receiver. We investigate channel estimation and equalization algorithms of ultra-wideband radio with pulse position modulation. We propose a completely blind channel estimation method based on the first-order cyclostationarity in the received signal. In contrast to other blind UWB channel estimation methods, our algorithm exhibits low complexity and is robust for channels with large numbers of taps. We investigate equalization by introducing a discrete-time equivalent model for time-hopping pulse-position-modulated UWB systems. This equivalent model views the transmitter-channel-receiver system at symbol rate. The computational complexity is reduced by processing the received data at symbol rate instead of chip rate. Symbol detection techniques including decision feedback equalization and maximum likelihood detection are evaluated and compared with correlation detection. Chapter 1 is an introduction to UWB systems, including the development of the technology, current research topics, and recent applications. Chapters 2 and 3 study the channel estimation and equalization problems, respectively. Chapter 4 summarizes the thesis and presents possible future work.

Author: Maise Tamouh Al Atassi
Publisher:
ISBN:
Category :
Languages : en
Pages : 100

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Due to the desirable characteristics of Ultra Wideband (UWB) signals, modern-day wireless communications systems are becoming increasingly designed to use such signals. However, UWB technology faces many challenges such as the extremely high sampling rate, the large channel length and the complicated receiver design. These challenges call for adopting a new technique that overcomes the demanding Shannon-Nyquist approach for sampling and allows for signal reconstructions using a fewer number of measurements, such as Compressed Sensing (CS). In this thesis, the theory of CS is employed as part of the UWB channel estimation process using greedy algorithms. We study the performance of a variety of greedy reconstruction algorithms including "Matching Pursuit" and "Weighted Matching Pursuit", under different types of measurement matrices while taking into consideration the effect of additive noise on the performance of the system. We propose two novel greedy reconstruction algorithms: "Block-wise Matching Pursuit" and "Bayesian Weighted Matching Pursuit", and prove that they outperform existing reconstruction algorithms in terms of execution time and power consumption.

Author: Ted C.-K. Liu
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Ultra-wideband (UWB) technology is the next viable solution for applications in wireless personal area network (WPAN), body area network (BAN) and wireless sensor network (WSN). However, as application evolves toward a more realistic situation, wideband channel characteristics such as pulse distortion must be accounted for in channel modeling. Furthermore, application-oriented services such as ranging and localization demand fast prototyping, real-time processing of measured data, and good low signal-to-noise ratio (SNR) performance. Despite the tremendous effort being vested in devising new receivers by the global research community, channel-estimating Rake receiver is still one of the most promising receivers that can offer superior performance to the suboptimal counterparts. However, acquiring Nyquist-rate samples costs substantial power and resource consumption and is a major obstacle to the feasible implementation of the asymptotic maximum likelihood (ML) channel estimator. In this thesis, we address all three aspects of the UWB impulse radio (UWB-IR), in three separate contributions. First, we study the {\it a priori} dependency of the CLEAN deconvolution with real-world measurements, and propose a high-resolution, multi-template deconvolution algorithm to enhance the channel estimation accuracy. This algorithm is shown to supersede its predecessors in terms of accuracy, energy capture and computational speed. Secondly, we propose a {\it regularized} least squares time-of-arrival (ToA) estimator with wavelet denoising to the problem of ranging and localization with UWB-IR. We devise a threshold selection framework based on the Neyman-Pearson (NP) criterion, and show the robustness of our algorithm by comparing with other ToA algorithms in both computer simulation and ranging measurements when advanced digital signal processing (DSP) is available. Finally, we propose a low-complexity ML (LC-ML) channel estimator to fully exploit the multipath diversity with Rake receiver with sub-Nyquist rate sampling. We derive the Cram\'er-Rao Lower Bound (CRLB) for the LC-ML, and perform simulation to compare our estimator with both the $\ell_1$-norm minimization technique and the conventional ML estimator.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
Ultra-wideband (UWB) technology is the next viable solution for applications in wireless personal area network (WPAN), body area network (BAN) and wireless sensor network (WSN). However, as application evolves toward a more realistic situation, wideband channel characteristics such as pulse distortion must be accounted for in channel modeling. Furthermore, application-oriented services such as ranging and localization demand fast prototyping, real-time processing of measured data, and good low signal-to-noise ratio (SNR) performance. Despite the tremendous effort being vested in devising new receivers by the global research community, channel-estimating Rake receiver is still one of the most promising receivers that can offer superior performance to the suboptimal counterparts. However, acquiring Nyquist-rate samples costs substantial power and resource consumption and is a major obstacle to the feasible implementation of the asymptotic maximum likelihood (ML) channel estimator. In this thesis, we address all three aspects of the UWB impulse radio (UWB-IR), in three separate contributions. First, we study the {\it a priori} dependency of the CLEAN deconvolution with real-world measurements, and propose a high-resolution, multi-template deconvolution algorithm to enhance the channel estimation accuracy. This algorithm is shown to supersede its predecessors in terms of accuracy, energy capture and computational speed. Secondly, we propose a {\it regularized} least squares time-of-arrival (ToA) estimator with wavelet denoising to the problem of ranging and localization with UWB-IR. We devise a threshold selection framework based on the Neyman-Pearson (NP) criterion, and show the robustness of our algorithm by comparing with other ToA algorithms in both computer simulation and ranging measurements when advanced digital signal processing (DSP) is available. Finally, we propose a low-complexity ML (LC-ML) channel estimator to fully exploit the multipath diversity with Rak.

Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 316

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"Education, arts and social sciences, natural and technical sciences in the United States and Canada".

Author:
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Category :
Languages : en
Pages : 4

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In order to access the viability of ultra-wideband communications for military applications, a framework for accurately analyzing system performance is required. This research project addresses the need for a tractable, outdoor ultra-wideband (UWB) channel model which will provide the foundation for performance evaluation an and the examination of various design tradeoffs that exist at the physical layer The other major thrusts of the research include channel estimation and error control coding which are essential to the successful realization of and implementation of UWB communication systems.

Author: 華文聖
Publisher:
ISBN:
Category :
Languages : en
Pages : 68

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Author: Maryam Vala
Publisher:
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Category :
Languages : en
Pages :

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"Ultra Wideband (UWB) is a rapidly growing technology for digital wireless communications. UWB utilizes low power, ultra short, pulses and is specifically suited for short-range, high-rate indoor wireless communications as well as fine localization applications. The attractive properties of UWB are a direct consequence of its very wide bandwidth that also implies an extremely high Nyquist sampling rate, so digital processing of UWB signals requires the use of fast and efficient, and therefore, expensive, Analog to Digital Converters. UWB systems are commonly used in indoor environments in which propagation is characterized by long but sparse multipath channels. Multi-path channels cause inter symbol interference (ISI) and introduce distortion to the received signal. To counter the effects of the channel, the channel impulse response must be accurately estimated at the receiver. There are two main estimation approaches for UWB channels: Compressed Sensing (CS)-based and Adaptive Filter (AF)-based. The former combine sampling and compression into a single linear measurement process that operates at sub-Nyquist rate by capitalizingon the sparsity of UWB signals. The latter, uses Least-Mean-Square filtering principles to obtain low complexity channel estimation methods. The problem we consider in this thesisis the estimation of a long sparse multi-path channel in an UWB system. We focus on systems that use Pulse Position Modulation (PPM) that is one of the most commonly used modulation schemes in UWB systems. We review CS and AF based methods and then we propose new AF-type methods specifically for the estimation of sparse multi-path channels with PPM inputs. The main idea behind the proposed methods is to estimate the long channel in sections in order to reduce the computational cost and improve the estimation performance. Finally, we present simulation results showing the superior performance of the proposed algorithms." --

Author: Yong Soo Cho
Publisher: John Wiley & Sons
ISBN: 0470825626
Category : Technology & Engineering
Languages : en
Pages : 458

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Book Description
MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). In MIMO-OFDM Wireless Communications with MATLAB®, the authors provide a comprehensive introduction to the theory and practice of wireless channel modeling, OFDM, and MIMO, using MATLAB® programs to simulate the various techniques on MIMO-OFDM systems. One of the only books in the area dedicated to explaining simulation aspects Covers implementation to help cement the key concepts Uses materials that have been classroom-tested in numerous universities Provides the analytic solutions and practical examples with downloadable MATLAB® codes Simulation examples based on actual industry and research projects Presentation slides with key equations and figures for instructor use MIMO-OFDM Wireless Communications with MATLAB® is a key text for graduate students in wireless communications. Professionals and technicians in wireless communication fields, graduate students in signal processing, as well as senior undergraduates majoring in wireless communications will find this book a practical introduction to the MIMO-OFDM techniques. Instructor materials and MATLAB® code examples available for download at www.wiley.com/go/chomimo