PreprintCC BY 4.0arXiv
Rates and Nearly-Lossless State over a Multi-Access Channel with Causal State Information
Abstract
The problem of transmitting both data and state over a memoryless state-dependent multi-access channel with causal state information is addressed. The state comprises three independent components: a common component, which is revealed to both en- coders, and two private components, each of which is revealed to a different encoder. The data are to be recovered with arbitrarily-small probability of error, and the state sequence with arbitrarily-small symbol-error rate. Under the assumption that the capacity region in the absence of a state recon- struction constraint is nonempty, the capacity region is derived and is shown to be achievable using a Block-Markov coding scheme employing binning and superposition coding.
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BibTeX
@misc{lapidoth2026rates,
title = {{Rates and Nearly-Lossless State over a Multi-Access Channel with Causal State Information}},
author = {Amos Lapidoth and Baohua Ni},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.41860},
eprint = {2610.41860},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.41860},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Rates and Nearly-Lossless State over a Multi-Access Channel with Causal State Information
AU - Amos Lapidoth
AU - Baohua Ni
PY - 2026
DA - 2026/10/30
PB - arXiv
DO - 10.48550/arxiv.2610.41860
UR - https://arxiv.org/abs/2610.41860
AB - The problem of transmitting both data and state over a memoryless state-dependent multi-access channel with causal state information is addressed. The state comprises three independent components: a common component, which is revealed to both en- coders, and two private components, each of which is revealed to a different encoder. The data are to be recovered with arbitrarily-small probability of error, and the state sequence with arbitrarily-small symbol-error rate. Under the assumption that the capacity region in the absence of a state recon- struction constraint is nonempty, the capacity region is derived and is shown to be achievable using a Block-Markov coding scheme employing binning and superposition coding.
ER -