Research
Multiuser information and coding theory
Information theoretic security
Communication theory
Information theory and statistics
Communication networks
Our research is in the field of multiuser information theory and
coding. It deals with the study of probabilistic models for
compression of multiple signals, reliable transmission among several
users and secure communication. The main objectives are
characterizations of the fundamental limits of performance, and
analysis of coding, modulation and signal processing techniques for
attaining this performance. Applications lie in a variety of
communication networks.
Our current research focuses on understanding
how in certain multiterminal system models, correlation among the signals
at network terminals can be exploited, through managed cooperation, in
designing efficient methods for signal sampling, compression,
transmission and assuring information security. Provable limits of
performance and techniques for achieving them are analyzed.
Specific research projects include:
samplingquantizationdistortion tradeoffs in statistical inference for
random field models; connections between common randomness generation by
multiple terminals, network secret key generation and secure function
computation; database privacy; and reliable communication over hybrid radio
frequency and free space optical communication systems.
See: Communication, Control and Signal Processing Seminar
Selected Publications
Multiterminal Secrecy by Public Discussion,
P. Narayan and H. Tyagi, Foundations and Trends in Communications and Information Theory, 2016.
Common Randomness for Secure Computing, P. Narayan, H. Tyagi and S. Watanabe,
Proceedings of the IEEE International Symposium on Information Theory, Hong Kong, 2015.
How Many Queries Will Resolve Common Randomness?,
H. Tyagi and P. Narayan,
IEEE Transactions on Information Theory, 2013.
Secrecy Generation for Multiaccess Channel Models,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 2013.
State Dependent Channels: Strong Converse and Bounds on Reliability Function,
H. Tyagi and P. Narayan,
Excursions in Harmonic Analysis: Applied and Numerical Harmonic
Analysis, Springer, 2013.
Secret Key Generation for Correlated Gaussian Sources,
S. Nitinawarat and P. Narayan,
IEEE Transactions on Information Theory, 2012.
Secret Key and Private Key Constructions for Simple Multiterminal Source Models,
C. Ye and P. Narayan,
IEEE Transactions on Information Theory, 2012.
Secret Key Generation for a Pairwise Independent Network Model,
S. Nitinawarat, C. Ye, A. Barg, P. Narayan and A. Reznik,
IEEE Transactions on Information Theory, 2010.
Capacity of a Shared Secret Key,
I. Csiszár and P. Narayan,
Proceedings of the IEEE International Symposium on Information Theory, Austin, Texas, 2010.
Secrecy Capacities for Multiterminal Channel Models,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 2008.
Active Pointing Control for Short Range FreeSpace Optical Communication,
A. Komaee, P.S. Krishnaprasad and P. Narayan,
Communications in Information and Systems, 2007.
The Poisson Fading Channel,
K. Chakraborty and P. Narayan,
IEEE Transactions on Information Theory, 2007.
Secrecy Capacities for Multiple Terminals,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 2004.
Order Estimation for a Special Class of Hidden Markov Sources and Binary
Renewal Processes,
S. Khudanpur and P. Narayan,
IEEE Transactions on Information Theory, 2002.
Capacities of TimeVarying MultipleAccess Channels with Side
Information,
A. Das and P. Narayan,
IEEE Transactions on Information Theory, 2002.
Common Randomness and Secret Key Generation with a Helper,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 2000.
Reliable Communication under Channel Uncertainty,
A. Lapidoth and P. Narayan,
IEEE Transactions on Information Theory, 1998.
The Optimal Error Exponent for Markov Order Estimation,
L. Finesso, C. Liu and P. Narayan,
IEEE Transactions on Information Theory, 1996.
Typicality of a Good RateDistortion Code,
A. Kanlis, S. Khudanpur and P. Narayan,
Problemy Peredachi Informatsii, 1996.
The Error Exponent for Successive Refinement by Partitioning,
A. Kanlis and P. Narayan,
IEEE Transactions on Information Theory, 1996.
Capacity of the Arbitrarily Varying Channel Under List Decoding,
V. Blinovsky, M.S. Pinsker and P. Narayan,
Problemy Peredachi Informatsii, 1995.
Channel Capacity for a Given Decoding Metric,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 1995.
Cutoff Rate Channel Design,
P. Narayan and D. Snyder,
Communication and Cryptography: Two Sides of One Tapestry, R. Blahut et al. (Eds.), Kluwer Publishers, Boston, 1994.
Order Estimation and Sequential Universal Data Compression of a Hidden
Markov Source via the Method of Mixtures,
C. Liu and P. Narayan,
IEEE Transactions on Information Theory, 1994.
Jointly Optimal Flow Control and Routing at a Simple Network Node,
I. Lambadaris and P. Narayan,
Stochastic Models, 1994.
Capacity of the Gaussian Arbitrarily Varying Channel,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 1991.
Capacity and Decoding Rules for Classes of Arbitrarily Varying
Channels,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 1989.
The Capacity of a Vector Gaussian Arbitrarily Varying Channel,
B.L. Hughes and P. Narayan,
IEEE Transactions on Information Theory, 1988.
The Capacity of the Arbitrary Varying Channel Revisited: Positivity,
Constraints,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 1988.
Arbitrarily Varying Channels with Constrained Inputs and States,
I. Csiszár and P. Narayan,
IEEE Transactions on Information Theory, 1988.
Signal Set Design for Bandlimited, Memoryless, MultipleAccess Channels
with Soft Decision Demodulation,
P. Narayan and D.L. Snyder,
IEEE Transactions on Information Theory, 1987.
Gaussian Arbitrarily Varying Channels,
B.L. Hughes and P. Narayan,
IEEE Transactions on Information Theory, 1987.
Estimation of the Rate of a DoublyStochastic, TimeSpace Poisson
Process,
J. Gubner and P. Narayan,
IMA Journal of Mathematical Control and Information, 1986.
The Two User Cutoff Rate Region for an Asynchronous and a Synchronous
Multiple Access Channel are the Same,
P. Narayan and D.L. Snyder,
IEEE Transactions on Information Theory, 1981.
