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arXiv 0802.0342cs.ITmath.IT
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网络容量定理中结构随机码的情形

The Case for Structured Random Codes in Network Capacity Theorems

Bobak Nazer, Michael Gastpar

摘要:

随机编码参数是大多数信道容量可扩展性证明的基础。在本文中,我们表明,在他们的标准形式,这样的参数是不够的证明一些网络容量定理:结构化的编码参数,如随机线性或格码,达到更高的速率。从历史上看,结构化代码一直被研究作为实际建设的垫脚石。然而,Körner和Marton通过推导分布式函数信源编码问题的最佳速率区域,证明了他们在容量定理中的有用性。在这里,我们使用有限域和高斯多路访问网络作为典型的例子来证明,即使我们想通过网络发送比特,结构化代码成功的简单随机代码失败。除了网络编码,我们还考虑了分布式计算在嘈杂的信道和一个特殊的中继类型的问题。

英文摘要:

Random coding arguments are the backbone of most channel capacity achievability proofs. In this paper, we show that in their standard form, such arguments are insufficient for proving some network capacity theorems: structured coding arguments, such as random linear or lattice codes, attain higher rates. Historically, structured codes have been studied as a stepping stone to practical constructions. However, Körner and Marton demonstrated their usefulness for capacity theorems through the derivation of the optimal rate region of a distributed functional source coding problem. Here, we use multicasting over finite field and Gaussian multiple-access networks as canonical examples to demonstrate that even if we want to send bits over a network, structured codes succeed where simple random codes fail. Beyond network coding, we also consider distributed computation over noisy channels and a special relay-type problem.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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