Arikan meets Shannon: Polar codes with near-optimal convergence to channel capacity

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Abstract

Let W be a binary-input memoryless symmetric (BMS) channel with Shannon capacity I(W) and fix any α > 0. We construct, for any sufficiently small δ> 0, binary linear codes of block length O(1/2+α) and rate I(W)-δthat enable reliable communication on W with quasi-linear time encoding and decoding. Shannon's noisy coding theorem established the existence of such codes (without efficient constructions or decoding) with block length O(1/2). This quadratic dependence on the gap δto capacity is known to be the best possible. Our result thus yields a constructive version of Shannon's theorem with near-optimal convergence to capacity as a function of the block length. This resolves a central theoretical challenge associated with the attainment of Shannon capacity. Previously such a result was only known for the binary erasure channel. Our codes are a variant of Arikan's polar codes based on multiple carefully constructed local kernels, one for each intermediate channel that arises in the decoding. A crucial ingredient in the analysis is a strong converse of the noisy coding theorem when communicating using random linear codes on arbitrary BMS channels. Our converse theorem shows extreme unpredictability of even a single message bit for random coding at rates slightly above capacity.

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APA

Guruswami, V., Riazanov, A., & Ye, M. (2020). Arikan meets Shannon: Polar codes with near-optimal convergence to channel capacity. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 552–564). Association for Computing Machinery. https://doi.org/10.1145/3357713.3384323

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