A digital fountain approach to reliable distribution of bulk data
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
The capacity of low-density parity-check codes under message-passing decoding
IEEE Transactions on Information Theory
Design of capacity-approaching irregular low-density parity-check codes
IEEE Transactions on Information Theory
Analysis of sum-product decoding of low-density parity-check codes using a Gaussian approximation
IEEE Transactions on Information Theory
Design methods for irregular repeat-accumulate codes
IEEE Transactions on Information Theory
Regular and irregular progressive edge-growth tanner graphs
IEEE Transactions on Information Theory
Raptor codes on binary memoryless symmetric channels
IEEE Transactions on Information Theory
Seamless rate adaptation for wireless networking
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
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We are interested in the analysis and optimization of Raptor codes under a joint decoding framework, that is, when the precode and the fountain code exchange soft information iteratively. We develop an analytical asymptotic convergence analysis of the joint decoder, derive an optimization method for the design of efficient output degree distributions, and show that the new optimized distributions outperform the existing ones, both at long and moderate lengths. We also show that jointly decoded Raptor codes are robust to channel variation: they perform reasonably well over a wide range of channel capacities. This robustness property was already known for the erasure channel but not for the Gaussian channel. Finally, we discuss some finite length code design issues. Contrary to what is commonly believed, we show by simulations that using a relatively low rate for the precode (Rp ≃ 0.9), we can improve greatly the error floor performance of the Raptor code.