Skip to main content

Capacity-achieving ensembles for the binary erasure channel with bounded complexity

Publication ,  Conference
Pfister, H; Sason, I; Urbanke, R
Published in: IEEE International Symposium on Information Theory - Proceedings
October 20, 2004

We present two sequences of ensembles of non-systematic irregular repeat-accumulate codes which asymptotically (as their block length tends to infinity) achieve capacity on the binary erasure channel (BEC) with bounded complexity. This is in contrast to all previous constructions of capacity-achieving sequences of ensembles whose complexity grows at least like the log of the inverse of the gap to capacity. The new bounded complexity result is achieved by allowing a sufficient number of state nodes in the Tanner graph representing the codes.

Duke Scholars

Published In

IEEE International Symposium on Information Theory - Proceedings

Publication Date

October 20, 2004

Start / End Page

207
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Pfister, H., Sason, I., & Urbanke, R. (2004). Capacity-achieving ensembles for the binary erasure channel with bounded complexity. In IEEE International Symposium on Information Theory - Proceedings (p. 207).
Pfister, H., I. Sason, and R. Urbanke. “Capacity-achieving ensembles for the binary erasure channel with bounded complexity.” In IEEE International Symposium on Information Theory - Proceedings, 207, 2004.
Pfister H, Sason I, Urbanke R. Capacity-achieving ensembles for the binary erasure channel with bounded complexity. In: IEEE International Symposium on Information Theory - Proceedings. 2004. p. 207.
Pfister, H., et al. “Capacity-achieving ensembles for the binary erasure channel with bounded complexity.” IEEE International Symposium on Information Theory - Proceedings, 2004, p. 207.
Pfister H, Sason I, Urbanke R. Capacity-achieving ensembles for the binary erasure channel with bounded complexity. IEEE International Symposium on Information Theory - Proceedings. 2004. p. 207.

Published In

IEEE International Symposium on Information Theory - Proceedings

Publication Date

October 20, 2004

Start / End Page

207