University of California, Riverside

Department of Electrical and Computer Engineering

Channel Estimation in Ultra Wideband Communications Using Up to the Second Order Statistics

Channel Estimation in Ultra Wideband Communications Using Up to the Second Order....

Jin Tang
Department of Electrical Engineering, UCR

Date: February 9, 2004
Time: 11:10 am
Location: Bourns Hall A265

With recent release of a large spectral mask (3.1GHz-10.6GHz frequency band) from the Federal Communications Commission, there emerges a lot of research and commercial interest in studying/applying the ultra-wideband (UWB) technology. Many of its appealing features, such as low power transmission, easy penetration of radio waves into materials and obstructs, high immunity to multipath propagation, very fine time resolution, make this technology a very competitive candidate for applications in high-rate wireless local area network (WLAN), wireless multimedia communications, and sensor networks. Despite its promising futures, there still exist many challenges that require significant research efforts.

In this talk, I will focus on channel estimation problems in time-hopping UWB communications. Although maximum likelihood techniques have been applied in the literature, they invoke a Gaussian assumption on the interference whose structure is disregarded, resulting in degraded performance. We introduce two methods based on the first-order and second-order statistics of received data, namely the mean and covariance matching (CM) based methods. By exploring structures of various interference components in a multipath environment including multi-user interference, inter-symbol interference and inter-fame interference, our estimators are shown to achieve superior performance. If pseudo-random time hopping sequences are used to enable multiple access, reliable estimates of mean and covariance cannot be obtained by conventional sample-average methods. However, those two methods are still applicable after some modifications of the cost functions. Reduced complexity single-user variants can be developed accordingly. Theoretical performance analysis and simulation results will be presented.


Jin Tang received the B.S. degree in electrical engineering and business administration from Beijing University of Aeronautics and Astronautics in 1995 and the M.S. degree in electrical engineering from the University of California, Riverside, in 2003. Before his graduate study, he worked in General Electrical (GE) and later in IBM Global Services as an information technology consultant. He has provided consulting services to many industry companies, including Motorola, Toshiba, China NetCom. He is now a Ph.D. candidate in the Electrical Engineering Department at the University of California, Riverside. His research interests include channel estimation, receiver design for ultra-wideband communication systems.
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