TY - GEN
T1 - Computationally Efficient Codes for Adversarial Binary-Erasure Channels
AU - Li, Sijie
AU - Krishnan, Prasad
AU - Jaggi, Sidharth
AU - Langberg, Michael
AU - Sarwate, Anand D.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - We study communication models for channels with erasures in which the erasure pattern can be controlled by an adversary with partial knowledge of the transmitted codeword. In particular, we design block codes for channels with binary inputs with an adversary who can erase a fraction p of the transmitted bits. We consider causal adversaries, who must choose to erase an input bit using knowledge of that bit and previously transmitted bits, and myopic adversaries, who can choose an erasure pattern based on observing the transmitted codeword through a binary erasure channel with random erasures. For both settings we design efficient (polynomial time) encoding and decoding algorithms that use randomization at the encoder only. Our constructions achieve capacity for the causal and "sufficiently myopic"models. For the "insufficiently myopic"adversary, the capacity is unknown, but existing converses show the capacity is zero for a range of parameters. For all parameters outside of that range, our construction achieves positive rates.
AB - We study communication models for channels with erasures in which the erasure pattern can be controlled by an adversary with partial knowledge of the transmitted codeword. In particular, we design block codes for channels with binary inputs with an adversary who can erase a fraction p of the transmitted bits. We consider causal adversaries, who must choose to erase an input bit using knowledge of that bit and previously transmitted bits, and myopic adversaries, who can choose an erasure pattern based on observing the transmitted codeword through a binary erasure channel with random erasures. For both settings we design efficient (polynomial time) encoding and decoding algorithms that use randomization at the encoder only. Our constructions achieve capacity for the causal and "sufficiently myopic"models. For the "insufficiently myopic"adversary, the capacity is unknown, but existing converses show the capacity is zero for a range of parameters. For all parameters outside of that range, our construction achieves positive rates.
UR - https://www.scopus.com/pages/publications/85171479180
U2 - 10.1109/ISIT54713.2023.10206731
DO - 10.1109/ISIT54713.2023.10206731
M3 - Conference contribution
AN - SCOPUS:85171479180
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 228
EP - 233
BT - 2023 IEEE International Symposium on Information Theory, ISIT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Symposium on Information Theory, ISIT 2023
Y2 - 25 June 2023 through 30 June 2023
ER -