TY - GEN
T1 - The arbitrarily varying degraded broadcast channel with causal side information at the encoder
AU - Pereg, Uzi
AU - Steinberg, Yossef
N1 - Funding Information: This work was supported by the Israel Science Foundation (grant No. 1285/16). Publisher Copyright: © 2017 IEEE.
PY - 2017/8/9
Y1 - 2017/8/9
N2 - In this work, we study the arbitrarily varying degraded broadcast channel (AVDBC), when state information is available at the transmitter in a causal manner. We establish inner and outer bounds on both the random code capacity region and the deterministic code capacity region. The capacity region is then determined for a class of channels satisfying a condition on the mutual informations between the strategy variables and the channel outputs. As an example, we show that the condition holds for the arbitrarily varying binary symmetric broadcast channel, and we find the corresponding capacity region.
AB - In this work, we study the arbitrarily varying degraded broadcast channel (AVDBC), when state information is available at the transmitter in a causal manner. We establish inner and outer bounds on both the random code capacity region and the deterministic code capacity region. The capacity region is then determined for a class of channels satisfying a condition on the mutual informations between the strategy variables and the channel outputs. As an example, we show that the condition holds for the arbitrarily varying binary symmetric broadcast channel, and we find the corresponding capacity region.
KW - Arbitrarily varying channel
KW - Causal state information
KW - Degraded broadcast channel
KW - Deterministic code
KW - Minimax theorem
KW - Random code
KW - Shannon strategies
KW - Side information
KW - Symmetrizability
UR - https://www.scopus.com/pages/publications/85034023312
U2 - 10.1109/ISIT.2017.8006685
DO - 10.1109/ISIT.2017.8006685
M3 - Conference contribution
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 1033
EP - 1037
BT - 2017 IEEE International Symposium on Information Theory, ISIT 2017
T2 - 2017 IEEE International Symposium on Information Theory, ISIT 2017
Y2 - 25 June 2017 through 30 June 2017
ER -