TY - GEN
T1 - Bayesian sequential detection for the BSC with unknown crossover probability
AU - Nelson, Jill K.
AU - Singer, Andrew C.
PY - 2006
Y1 - 2006
N2 - We propose a novel scheme for detecting coded data transmitted over a communication channel that is either partially or entirely unknown. Viewing the unknown channel parameters as stochastic quantities drawn from a known probability distribution, the likelihood of a sequence of data is derived using Bayesian techniques. A stack-like tree search algorithm is proposed for implementation of maximum likelihood (ML) sequence detection under the Bayesian metric. We apply the Bayesian scheme to the binary symmetric channel (BSC) with unknown crossover probability. The structure of the resulting metric is compared to both the conventional Fano metric and a universal metric presented in (Lapidoth and Ziv, IEEE Trans. IT 1999). Based on its relationship to the metric developed by Lapidoth and Ziv, the newly-derived metric is shown to be pairwise universal over the ensemble of random uniform codes.
AB - We propose a novel scheme for detecting coded data transmitted over a communication channel that is either partially or entirely unknown. Viewing the unknown channel parameters as stochastic quantities drawn from a known probability distribution, the likelihood of a sequence of data is derived using Bayesian techniques. A stack-like tree search algorithm is proposed for implementation of maximum likelihood (ML) sequence detection under the Bayesian metric. We apply the Bayesian scheme to the binary symmetric channel (BSC) with unknown crossover probability. The structure of the resulting metric is compared to both the conventional Fano metric and a universal metric presented in (Lapidoth and Ziv, IEEE Trans. IT 1999). Based on its relationship to the metric developed by Lapidoth and Ziv, the newly-derived metric is shown to be pairwise universal over the ensemble of random uniform codes.
UR - https://www.scopus.com/pages/publications/39049134865
U2 - 10.1109/ISIT.2006.261863
DO - 10.1109/ISIT.2006.261863
M3 - Conference contribution
AN - SCOPUS:39049134865
SN - 1424405041
SN - 9781424405046
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 640
EP - 644
BT - Proceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006
T2 - 2006 IEEE International Symposium on Information Theory, ISIT 2006
Y2 - 9 July 2006 through 14 July 2006
ER -