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arXiv 1202.6086cs.ITcs.CCmath.COmath.IT
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平均半径列表译码的组合限制

Combinatorial limitations of average-radius list-decoding

Venkatesan Guruswami, Srivatsan Narayanan

摘要:

我们研究了列表解码的某些组合方面,其动机是已知的上限($O(1/γ)$的)和下限($Ω_p(\log (1/γ))$的)之间的指数差距,用于以远离容量的速率$γ$解码高达半径$p$所需的列表大小,即,$1-\h(p)-γ$(此处为$p\in (0,1/2)$和$γ> 0$)。我们的主要结果如下:我们证明了在任何速率为$1-\h(p)-γ$的二进制码$C \subseteq \{0,1\}^n$中,一定存在一个$Ω_p(1/\sqrtγ)$码字的集合$\mathcal{L} \subset C$,使得$\mathcal{L}$中的点到它们的质心的平均距离至多为$pn$。换句话说,必须存在具有低“平均半径”的$Ω_p(1/\sqrtγ)$码字。“列表解码的标准概念对应于使用码字集合到中心的最大距离而不是平均距离。平均半径形式本身是很自然的,并且是由经典的约翰逊界限所暗示的。剩下的结果涉及列表解码的标准概念,并有助于澄清列表解码的组合景观:1。我们给一个简短的简单的证明,在所有固定的字母表,上述$Ω_p(\log (γ))$下界。早些时候,这个界限是由布利诺夫斯基的一个复杂的、更一般的结果得出的。2.我们表明,一个{ \em不能}提高$Ω_p(\log (1/γ))$下界通过技术的基础上确定的零速率制度的列表解码的恒定重量的代码。3.我们展示了一个“反向连接”,表明列表解码的常重码意味着具有更高速率的列表解码的通用码。4.我们给出简单的二阶矩为基础的证明紧(常数因子)的列表解码随机码和随机线性码的错误以及擦除所需的列表大小的下界。

英文摘要:

We study certain combinatorial aspects of list-decoding, motivated by the exponential gap between the known upper bound (of $O(1/γ)$) and lower bound (of $Ω_p(\log (1/γ))$) for the list-size needed to decode up to radius $p$ with rate $γ$ away from capacity, i.e., $1-\h(p)-γ$ (here $p\in (0,1/2)$ and $γ> 0$). Our main result is the following: We prove that in any binary code $C \subseteq \{0,1\}^n$ of rate $1-\h(p)-γ$, there must exist a set $\mathcal{L} \subset C$ of $Ω_p(1/\sqrtγ)$ codewords such that the average distance of the points in $\mathcal{L}$ from their centroid is at most $pn$. In other words, there must exist $Ω_p(1/\sqrtγ)$ codewords with low "average radius." The standard notion of list-decoding corresponds to working with the maximum distance of a collection of codewords from a center instead of average distance. The average-radius form is in itself quite natural and is implied by the classical Johnson bound. The remaining results concern the standard notion of list-decoding, and help clarify the combinatorial landscape of list-decoding: 1. We give a short simple proof, over all fixed alphabets, of the above-mentioned $Ω_p(\log (γ))$ lower bound. Earlier, this bound followed from a complicated, more general result of Blinovsky. 2. We show that one {\em cannot} improve the $Ω_p(\log (1/γ))$ lower bound via techniques based on identifying the zero-rate regime for list decoding of constant-weight codes. 3. We show a "reverse connection" showing that constant-weight codes for list decoding imply general codes for list decoding with higher rate. 4. We give simple second moment based proofs of tight (up to constant factors) lower bounds on the list-size needed for list decoding random codes and random linear codes from errors as well as erasures.

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