TY - GEN
T1 - One Shot Joint Source Channel Coding
AU - Elkayam, Nir
AU - Feder, Meir
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper presents a one shot analysis to the lossless joint source channel coding problem. Achievable and converse bounds are derived. Both bound are given in term of F(z), the CDF of the random variable Z=-log pe(V, X, Y) where pe(V, X, Y) is the the pairwise error probability between two codewords associated with two source symbols. This is an information functional that resembles a similar quantity in the meta-converse form of one shot channel coding, but it depends also on the source V in addition to the input X and the output Y of the channel. The role of F(z) is analogous to the role of the information spectrum, but our treatment does not include any asymptotic analysis. Relation to other known bounds is also demonstrated.
AB - This paper presents a one shot analysis to the lossless joint source channel coding problem. Achievable and converse bounds are derived. Both bound are given in term of F(z), the CDF of the random variable Z=-log pe(V, X, Y) where pe(V, X, Y) is the the pairwise error probability between two codewords associated with two source symbols. This is an information functional that resembles a similar quantity in the meta-converse form of one shot channel coding, but it depends also on the source V in addition to the input X and the output Y of the channel. The role of F(z) is analogous to the role of the information spectrum, but our treatment does not include any asymptotic analysis. Relation to other known bounds is also demonstrated.
UR - http://www.scopus.com/inward/record.url?scp=85202897082&partnerID=8YFLogxK
U2 - 10.1109/ISIT57864.2024.10619100
DO - 10.1109/ISIT57864.2024.10619100
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AN - SCOPUS:85202897082
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 623
EP - 628
BT - 2024 IEEE International Symposium on Information Theory, ISIT 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Symposium on Information Theory, ISIT 2024
Y2 - 7 July 2024 through 12 July 2024
ER -