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

We propose a joint list decoder and language decoder that exploits the redundancy of language-based sources during 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 the decoding of every few bits. 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. We show that if the language structure can be modeled as erasure correcting outer block codes, the rate of inner polar code can be increased while still guaranteeing a vanishing probability of error. To facilitate practical joint decoding, we first propose a construction of a dynamic dictionary using a trie and show an efficient way to trace the dictionary during decoding. Then we propose a joint decoding scheme for 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. Simulation results show that the joint decoding schemes outperform stand-alone polar codes with CRC-aided successive cancellation list decoding by over 0.6 dB.