Joint source-channel optimization of vector quantization with polar codes

Mohammad Sadegh Mohammadi, Eryk Dutkiewicz, Qi Zhang

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review


Joint application of polar channel coding combined with vector quantization lossy source coding is considered in this paper. The existing index assignment schemes in the literature cannot be used with polar codes due to their unique crossover probabilities. We elaborate on this problem and locally optimize index assignments. In addition, we propose an algorithm that jointly optimizes the number of quantization levels and the rate of the polar code in order to achieve minimum end-to-end distortion. It finds the optimal tradeoff between the distortion caused by channel errors and the quantization distortion. We also derive estimates for the crossover probabilities of the polar code which are required in the analysis. Simulation results confirm the effectiveness of the proposed algorithms and the accuracy of the crossover probabilities.

Original languageEnglish
Title of host publication2016 IEEE 84th Vehicular Technology Conference (VTC Fall)
Subtitle of host publicationproceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9781509017010
ISBN (Print)9781509017027
Publication statusPublished - 2016
Externally publishedYes
Event84th IEEE Vehicular Technology Conference, VTC Fall 2016 - Montreal, Canada
Duration: 18 Sep 201621 Sep 2016


Other84th IEEE Vehicular Technology Conference, VTC Fall 2016


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