Exact Moderate Deviation Asymptotics in Streaming Data Transmission

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 <inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> 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 remainder term in the exponent is carefully characterized. For the achievability proof, a known coding technique that involves a joint encoding and decoding of fresh and past messages is applied with some manipulations in the error analysis.