Computer Science – Information Theory
Scientific paper
2009-03-02
Computer Science
Information Theory
15 pages, submitted to Transactions on Information Theory
Scientific paper
We consider lossy source compression of a binary symmetric source using polar codes and the low-complexity successive encoding algorithm. It was recently shown by Arikan that polar codes achieve the capacity of arbitrary symmetric binary-input discrete memoryless channels under a successive decoding strategy. We show the equivalent result for lossy source compression, i.e., we show that this combination achieves the rate-distortion bound for a binary symmetric source. We further show the optimality of polar codes for various problems including the binary Wyner-Ziv and the binary Gelfand-Pinsker problem
Korada Satish Babu
Urbanke Rudiger
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