Polar Codes are Optimal for Lossy Source Coding
Satish Babu Korada, Rudiger L. Urbanke · IEEE Transactions on Information Theory · 2010
We consider lossy source compression of a binary symmetric source using polar codes and a 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 multiterminal problems including the binary Wyner-Ziv and the binary Gelfand-Pinsker problems. Our results extend to general versions of these problems.