| Abstract: |
Messages coded and transmitted over a channel usually contain some
redundancy which is usually not utilized by channel decoding techniques,
especially if the governing statistical parameters are unknown. We
propose to integrate universal lossless source coding techniques and
source parameter estimation into channel decoding of redundant sequences
with unknown statistics to improve decoding performance. We apply this
idea to Viterbi decoding of convolutional codes, turbo decoding of
systematic and non-systematic turbo codes, and to decoding of low density
parity check (LDPC) codes. This is done for the i.i.d. case, where the
coded data sequence has an i.i.d. distribution, but also (using more
advanced compression techniques) to more complex sequence models.
Simulation results demonstrate that we achieve bit error rate (BER)
performance very close to that achieved by non-universal techniques that
utilize prior knowledge of known message statistics. Furthermore, if
redundancy exists even in an unknown form, we can improve the code
performance over standard decoding. While we observe improvement in
systematic codes as well as in non-systematic codes, the most significant
improvement occurs with non-systematic codes. However, in order to
achieve this significant performance gain, we must also consider design of
proper non-systematic codes as well as of their decoding algorithms.
|
| Bio: |
Gil Shamir was born in Haifa, Israel in 1968. He received the B.Sc. (Cum
Laude), and M.Sc. degrees from the Technion, Israel Institute of
Technology, Haifa, Israel in 1990 and 1997, respectively, and the Ph.D.
degree from the University of Notre Dame, Notre Dame, IN, U.S.A. in 2000,
all in electrical engineering.
From 1990 to 1995 he participated in research and development of signal
processing and communication systems. From 1995 to 1997 he was with the
Electrical Engineering Department at the Technion - Israel Institute of
Technology, as a graduate student and teaching assistant. From September
1997 to May 2000 he was a Ph.D. student and a research assistant in the
Electrical Engineering Department at the University of Notre Dame, and
then a post-doctoral fellow until July 2001. During his tenure at Notre
Dame he was a fellow of the Center for Applied Mathematics of the
university. He is currently an assistant professor in the Electrical and
Computer Engineering Department at the University of Utah. His main
research interests include information theory, source coding, channel
coding, joint source-channel coding, and communication systems design.
Dr. Shamir received an NSF CAREER award in 2003.
|