Joint Source-Channel Optimization of Vector Quantization with Polar Codes

Mohammad Sadegh Mohammadi, Eryk Dutkiewicz, Qi Zhang

    Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-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 2016 - Proceedings : VTC-Fall
    Number of pages6
    Publication date2016
    Article number7881061
    ISBN (Print)978-1-5090-1701-0
    ISBN (Electronic)9781509017010
    Publication statusPublished - 2016
    EventIEEE Vehicular Technology Conference 2016 - Hotel Montreal Bonaventure, Montreal, Canada
    Duration: 18 Sept 201621 Sept 2016


    ConferenceIEEE Vehicular Technology Conference 2016
    LocationHotel Montreal Bonaventure
    Internet address


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