TY - GEN

T1 - Expansion coding

T2 - 2012 IEEE International Symposium on Information Theory, ISIT 2012

AU - Koyluoglu, O. Ozan

AU - Appaiah, Kumar

AU - Si, Hongbo

AU - Vishwanath, Sriram

PY - 2012

Y1 - 2012

N2 - A general method of coding over expansions is proposed, which allows one to reduce the highly non-trivial problem of coding over continuous channels to a much simpler discrete ones. More specifically, the focus is on the additive exponential noise (AEN) channel, for which the (binary) expansion of the (exponential) noise random variable is considered. It is shown that each of the random variables in the expansion corresponds to independent Bernoulli random variables. Thus, each of the expansion levels (of the underlying channel) corresponds to a binary symmetric channel (BSC), and the coding problem is reduced to coding over these parallel channels while satisfying the channel input constraint. This optimization formulation is stated as the achievable rate result, for which a specific choice of input distribution is shown to achieve a rate which is arbitrarily close to the channel capacity in the high SNR regime. Remarkably, the scheme allows for low-complexity capacity-achieving codes for AEN channels, using the codes that are originally designed for BSCs. Extensions to different channel models and applications to other coding problems are discussed.

AB - A general method of coding over expansions is proposed, which allows one to reduce the highly non-trivial problem of coding over continuous channels to a much simpler discrete ones. More specifically, the focus is on the additive exponential noise (AEN) channel, for which the (binary) expansion of the (exponential) noise random variable is considered. It is shown that each of the random variables in the expansion corresponds to independent Bernoulli random variables. Thus, each of the expansion levels (of the underlying channel) corresponds to a binary symmetric channel (BSC), and the coding problem is reduced to coding over these parallel channels while satisfying the channel input constraint. This optimization formulation is stated as the achievable rate result, for which a specific choice of input distribution is shown to achieve a rate which is arbitrarily close to the channel capacity in the high SNR regime. Remarkably, the scheme allows for low-complexity capacity-achieving codes for AEN channels, using the codes that are originally designed for BSCs. Extensions to different channel models and applications to other coding problems are discussed.

UR - http://www.scopus.com/inward/record.url?scp=84867497945&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84867497945&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2012.6283635

DO - 10.1109/ISIT.2012.6283635

M3 - Conference contribution

AN - SCOPUS:84867497945

SN - 9781467325790

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 1932

EP - 1936

BT - 2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012

Y2 - 1 July 2012 through 6 July 2012

ER -