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Ar?kan meets Shannon: Polar codes with near-optimal convergence to channel capacity

机译:Ar?kan与Shannon会合:极化码,信道容量接近最佳收敛

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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.
机译:设W为具有香农容量I(W)的二进制输入无记忆对称(BMS)通道,并固定任何0“>0。对于任何足够小的0”> 0,我们构造块长度为O(1 2的二进制线性代码+)和率I(W)?通过准线性时间编码和解码实现W上的可靠通信。香农的噪声编码定理确定了此类代码的存在(无有效构造或解码),其块长为O(1 2)。众所周知,这种对容量差距的二次依赖是最好的。因此,我们的结果得出了香农定理的建设性版本,其容量与块长度的函数接近最佳收敛。这解决了与获得香农能力有关的中心理论挑战。以前,这种结果仅在擦除通道中才知道。我们的代码是Arikan极性代码的一种变体,它基于多个精心构造的本地内核,每个内核在解码时都会出现一个。当在任意BMS通道上使用随机线性代码进行通信时,分析中的关键要素是噪声编码定理的强反。我们的逆定理表明,即使是单个消息位,对于以略高于容量的速率进行随机编码,也具有极端的不可预测性。

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