On Ultra Wideband Channel Estimation Using Compressed Sensing
Author | : Maise Tamouh Al Atassi |
Publisher | : |
Total Pages | : 100 |
Release | : 2011 |
ISBN-10 | : OCLC:788258617 |
ISBN-13 | : |
Rating | : 4/5 (17 Downloads) |
Book excerpt: 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.