Exact Moderate Deviation Asymptotics in Streaming Data Transmission
Si-Hyeon Lee, Vincent Y. F. Tan, and Ashish Khisti

TL;DR
This paper analyzes the fundamental limits of streaming data transmission in the moderate deviations regime, showing that the error exponent improves proportionally with the delay T for output symmetric channels.
Contribution
It establishes the exact moderate deviations constant for streaming transmission, demonstrating a T-fold improvement over non-streaming setups, and introduces a new change-of-measure lemma for the converse proof.
Findings
Moderate deviations constant is T times larger for streaming over non-streaming.
Error probability bounds are derived using a new change-of-measure lemma.
Achievability is shown with joint encoding and decoding of current and past messages.
Abstract
In this paper, a streaming transmission setup is considered where an encoder observes a new message in the beginning of each block and a decoder sequentially decodes each message after a delay of blocks. In this streaming setup, the fundamental interplay between the coding rate, the error probability, and the blocklength in the moderate deviations regime is studied. For output symmetric channels, the moderate deviations constant is shown to improve over the block coding or non-streaming setup by exactly a factor of for a certain range of moderate deviations scalings. For the converse proof, a more powerful decoder to which some extra information is fedforward is assumed. The error probability is bounded first for an auxiliary channel and this result is translated back to the original channel by using a newly developed change-of-measure lemma, where the speed of decay of the…
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