Joint Source-Channel Decoding of Polar Codes for Language-Based Source

TL;DR

This paper introduces a joint source-channel decoding method for polar codes that leverages language source redundancy and a dynamic dictionary to improve decoding accuracy without increasing complexity.

Contribution

It proposes a novel joint decoding scheme using a trie-based dictionary and an adaptive list size, enhancing polar code decoding by integrating source information.

Findings

Outperforms CRC-aided polar list decoding by over 0.6 dB.

Maintains same complexity as standard polar list decoding.

Reduces decoding errors in early stages through joint source-channel decoding.

Abstract

We exploit the redundancy of the language-based source to help polar decoding. By judging the validity of decoded words in the decoded sequence with the help of a dictionary, the polar list decoder constantly detects erroneous paths after every few bits are decoded. This path-pruning technique based on joint decoding has advantages over stand-alone polar list decoding in that most decoding errors in early stages are corrected. In order to facilitate the joint decoding, we first propose a construction of dynamic dictionary using a trie and show an efficient way to trace the dictionary during decoding. Then we propose a joint decoding scheme of polar codes taking into account both information from the channel and the source. The proposed scheme has the same decoding complexity as the list decoding of polar codes. A list-size adaptive joint decoding is further implemented to largely reduce the decoding complexity. We conclude by simulation that the joint decoding schemes outperform stand-alone polar codes with CRC-aided successive cancellation list decoding by over 0.6 dB.