TY - GEN
T1 - Random-coding error exponent of variable-length codes with a single-bit noiseless feedback
AU - Ginzach, Shai
AU - Merhav, Neri
AU - Sason, Igal
N1 - Publisher Copyright: © 2017 IEEE.
PY - 2017
Y1 - 2017
N2 - We study the random-coding error exponent function of variable-length codes in the presence of a noiseless feedback channel, which is allowed to be used merely for a single bit feedback per each transmitted message. In this study, we harness results and analysis techniques from the theory of sequential hypothesis testing, and combine them with modern distance enumeration methods which are used in the literature on error exponents. For this setup, sometimes referred to as stop-feedback, we derive an exact single-letter expression for the random-coding error exponent over the binary symmetric channel. For symmetric discrete memoryless channels, the exact error exponent at zero rate is obtained, and a lower bound is provided for any other positive rate below capacity.
AB - We study the random-coding error exponent function of variable-length codes in the presence of a noiseless feedback channel, which is allowed to be used merely for a single bit feedback per each transmitted message. In this study, we harness results and analysis techniques from the theory of sequential hypothesis testing, and combine them with modern distance enumeration methods which are used in the literature on error exponents. For this setup, sometimes referred to as stop-feedback, we derive an exact single-letter expression for the random-coding error exponent over the binary symmetric channel. For symmetric discrete memoryless channels, the exact error exponent at zero rate is obtained, and a lower bound is provided for any other positive rate below capacity.
UR - http://www.scopus.com/inward/record.url?scp=85046340307&partnerID=8YFLogxK
U2 - 10.1109/ITW.2017.8278012
DO - 10.1109/ITW.2017.8278012
M3 - منشور من مؤتمر
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 584
EP - 588
BT - 2017 IEEE Information Theory Workshop, ITW 2017
T2 - 2017 IEEE Information Theory Workshop, ITW 2017
Y2 - 6 November 2017 through 10 November 2017
ER -