Author: Solomon NunooPublisher:
ISBN:
Category :
Languages : en
Pages : 157
Book Description
Adaptive Channel Estimation for Sparse Ultra Wideband Systems
Author: Solomon NunooEstimation of Sparse Channels in IR-UWB Systems
Author: Maryam ValaPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
"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." --
Sparse Channel Estimation Based on Compressed Sensing Theory for UWB Systems
Author: Eva Lagunas TargaronaSparse Signal Processing for Massive MIMO Communications
Author: Zhen GaoPublisher: Springer Nature
ISBN: 9819953944
Category :
Languages : en
Pages : 225
Book Description
Artificial Intelligence and Robotics
Author: Huimin LuPublisher: Springer Nature
ISBN: 303056178X
Category : Technology & Engineering
Languages : en
Pages : 265
Book Description
This book provides insights into research in the field of artificial intelligence in combination with robotics technologies. The integration of artificial intelligence and robotic technologies is a highly topical area for researchers and developers from academia and industry around the globe, and it is likely that artificial intelligence will become the main approach for the next generation of robotics research. The tremendous number of artificial intelligence algorithms and big data solutions has significantly extended the range of potential applications for robotic technologies, and has also brought new challenges for the artificial intelligence community. Sharing recent advances in the field, the book features papers by young researchers presented at the 4th International Symposium on Artificial Intelligence and Robotics 2019 (ISAIR2019), held in Daegu, Korea, on August 20–24, 2019.
Channel Estimation and Equalization for Transmitted-Reference Ultra-Wideband Systems
Author: 華文聖Channel Estimation and Equalization for Ultra-wideband Communications with Pulse Position Modulation
Author: Xiaofan YangPublisher:
ISBN:
Category :
Languages : en
Pages : 94
Book Description
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.
Robust Channel Estimation for Ultra-wideband Communication Systems Using H [infinity] Algorithm
![Robust Channel Estimation for Ultra-wideband Communication Systems Using H [infinity] Algorithm PDF](https://books.google.com/books/content/images/frontcover/uZgvcgAACAAJ?fife=w80-h100)
Author: Witty WongOn Ultra Wideband Channel Estimation Using Compressed Sensing
Author: Maise Tamouh Al AtassiPublisher:
ISBN:
Category :
Languages : en
Pages : 100
Book Description
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.
Compressive Sensing for Wireless Networks
Author: Zhu HanPublisher: Cambridge University Press
ISBN: 1107018838
Category : Computers
Languages : en
Pages : 308
Book Description
This comprehensive reference delivers the understanding and skills needed to take advantage of compressive sensing in wireless networks.