Network coding with computation alignment

Naveen Goela, Changho Suh, M. Gastpar
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引用次数: 6

Abstract

Determining the capacity of multi-receiver networks with arbitrary message demands is an open problem in the network coding literature. In this paper, we consider a multi-source, multi-receiver symmetric deterministic network model parameterized by channel coefficients (inspired by wireless network flow) in which the receivers compute a sum of the symbols generated at the sources. Scalar and vector linear coding strategies are analyzed. It is shown that computation alignment over finite field vector spaces is necessary to achieve the computation capacities in the network. To aid in the construction of coding strategies, network equivalence theorems are established for the decomposition of deterministic models into elementary sub-networks. The linear coding capacity for computation is characterized for all channel parameters considered in the model for a countably infinite class of networks. The constructive coding schemes introduced herein for a specific class of networks provide an optimistic viewpoint for the application of structured codes in network communication.
网络编码与计算对齐
确定具有任意消息需求的多接收网络的容量是网络编码文献中的一个开放性问题。在本文中,我们考虑了一个由信道系数参数化的多源、多接收机对称确定性网络模型(受无线网络流的启发),其中接收机计算源处产生的符号的和。分析了标量和矢量线性编码策略。结果表明,在有限场向量空间上进行计算对齐是实现网络计算能力的必要条件。为了帮助编码策略的构建,建立了将确定性模型分解为基本子网络的网络等价定理。对一类可数无限网络,对模型中所考虑的所有信道参数的线性编码计算能力进行了表征。本文介绍的针对特定网络类型的结构化编码方案为结构化编码在网络通信中的应用提供了一个乐观的观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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