A general computation rule for lossy summaries/messages with examples from equalization
Junli Hu, Hans-Andrea Loeliger, Justin Dauwels, and Frank Kschischang
TL;DR
This paper introduces a general computation rule for lossy message summaries, notably converting soft-bit messages to Gaussian messages, which enhances Kalman equalizer performance in communication systems.
Contribution
It presents a novel, general method for lossy message computation, extending prior work and improving equalizer performance in communications.
Findings
Improved Kalman equalizer performance for uncoded transmission
Enhanced performance for coded transmission
Effective conversion of soft-bit to Gaussian messages
Abstract
Elaborating on prior work by Minka, we formulate a general computation rule for lossy messages. An important special case (with many applications in communications) is the conversion of "soft-bit" messages to Gaussian messages. By this method, the performance of a Kalman equalizer is improved, both for uncoded and coded transmission.
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Taxonomy
TopicsError Correcting Code Techniques · Algorithms and Data Compression · DNA and Biological Computing