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  • 标题:Ar?kan meets Shannon: Polar codes with near-optimal convergence to channel capacity
  • 本地全文:下载
  • 作者:Venkatesan Guruswami ; Andrii Riazanov ; Min Ye
  • 期刊名称:Electronic Colloquium on Computational Complexity
  • 印刷版ISSN:1433-8092
  • 出版年度:2019
  • 卷号:2019
  • 页码:1-67
  • 出版社:Universität Trier, Lehrstuhl für Theoretische Computer-Forschung
  • 摘要:

    Let W be a binary-input memoryless symmetric (BMS) channel with Shannon capacity I ( W ) and fix any 0"> 0 . We construct, for any sufficiently small 0"> 0 , binary linear codes of block length O (1 2+ ) and rate I ( W ) − that 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 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 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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