Arıkan meets Shannon: Polar codes with near-optimal convergence to channel capacity
November 10, 2019 · Declared Dead · 🏛 Symposium on the Theory of Computing
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Authors
Venkatesan Guruswami, Andrii Riazanov, Min Ye
arXiv ID
1911.03858
Category
cs.IT: Information Theory
Cross-listed
cs.CC,
cs.DS
Citations
24
Venue
Symposium on the Theory of Computing
Last Checked
5 months ago
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 $O(1/δ^{2+α})$ and rate $I(W)-δ$ that enable reliable communication on $W$ with quasi-linear time encoding and decoding. Shannon's noisy coding theorem established the \emph{existence} of such codes (without efficient constructions or decoding) with block length $O(1/δ^2)$. This quadratic dependence on the gap $δ$ to capacity is known to be 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 erasure channel. Our codes are a variant of Arıkan'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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