报告题目: |
Challenges in Wireless Mobile Adhoc Networks |
报告人: |
Lizhong Zheng |
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Associate professor,MIT
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报告时间: |
2006-12-29 09:50 |
报告地点: |
东主楼11区309 |
主办单位: |
清华大学电子工程系 |
简介: |
This two part talk will start with an overview of the main challenges of the
research in wireless networks, and the role of information theory in this
research. We argue that in order to break the boundary of Shannon?s
conventional information theory, we need to consider a new coding structure,
where coding algorithms and performance metrics are based on a novel way of
taking limits. The second part of the talk focus on a specific example of our
approach, applied to wideband communications. While capacity in the limit of
vanishing SNR per degree of freedom is known to be linear in SNR for fading and
non-fading channels, regardless of channel side information at the receiver,
such asymptotic results hide the cost of channel variability in terms of
performance. In this talk, rather than maintain a fixed channel model with a
given coherence and consider a vanishing SNR, we present a model in which
coherence, peak energy and SNR are considered jointly. With a novel way of
asymptotic analysis, we describe the effect of the relation between bandwidth,
channel variation, and peak power constraints on the performance of a wideband
system, characterized by the tradeoff between energy efficiency and spectral
efficiency.
Lizhong Zheng received the B.S and M.S. degrees, in 1994 and 1997 respectively,
from the Department of Electronic Engineering, Tsinghua University, China, ,
and the Ph.D. degree, in 2002, from the Department of Electrical Engineering
and Computer Sciences, University of California, Berkeley. Since 2002, he has
been working in the Department of Electrical Engineering and Computer Sciences
and the Laboratory of Information and Decision Systems at Massachusetts
Institute of Technology, where he is currently the KDD associate professor. His
research interests include information theory, wireless communications and
wireless networks. He received Eli Jury award from UC Berkeley in 2002, IEEE
Information Theory Society Paper Award in 2003, and NSF CAREER award in 2004.
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