EURASIP Journal on Applied Signal Processing
IEEE Transactions on Communications
Belief propagation with Gaussian priors for pilot-assisted communication over fading ISI channels
IEEE Transactions on Wireless Communications
Iterative channel and data estimation: framework and analysis via replica method
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
Blind per-state detection of DPSK over correlated fading channels
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
Monte Carlo solutions for blind phase noise estimation
EURASIP Journal on Wireless Communications and Networking - Special issue on synchronization in wireless communications
On asymptotic performance of iterative channel and data estimation in large DS-CDMA systems
WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
Adaptive iterative detectors for phase-uncertain channels via variational bounding
IEEE Transactions on Communications
How much training is needed for iterative multiuser detection and decoding
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
A systematic framework for iterative maximum likelihood receiver design
IEEE Transactions on Communications
Channel estimation by inference on Gaussian Markov random fields
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Interior point decoding for linear vector channels based on convex optimization
IEEE Transactions on Information Theory
Code-aided maximum-likelihood ambiguity resolution through free-energy minimization
IEEE Transactions on Signal Processing
EURASIP Journal on Wireless Communications and Networking
Information, Divergence and Risk for Binary Experiments
The Journal of Machine Learning Research
LDPC codes for fading channels: two strategies
AAECC'06 Proceedings of the 16th international conference on Applied Algebra, Algebraic Algorithms and Error-Correcting Codes
Iterative decoding in Factor Graph representation using Particle Filtering
Digital Signal Processing
| Hi-index | 754.90 |
Iterative algorithms are an attractive approach to approximating optimal, but high-complexity, joint channel estimation and decoding receivers for communication systems. We present a unified approach based on factor graphs for deriving iterative message-passing receiver algorithms for channel estimation and decoding. For many common channels, it is easy to find simple graphical models that lead directly to implementable algorithms. Canonical distributions provide a new, general framework for handling continuous variables. Example receiver designs for Rayleigh fading channels with block or Markov memory, and multipath fading channels with fixed unknown coefficients illustrate the effectiveness of our approach