中国邮电高校学报(英文) ›› 2009, Vol. 16 ›› Issue (2): 53-57.doi: 10.1016/S1005-8885(08)60201-0

• Networks • 上一篇    下一篇

Nonlinear network coding based on multiplication and exponentiation in GF(2m)

蒋安友,ZHU Jin-kang   

  1. PCN and SS Laboratory, Department of Electronics Engineering and Science Information, University of Science and Technology of China, Hefei 230027, China
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-04-30
  • 通讯作者: 蒋安友

Nonlinear network coding based on multiplication and exponentiation in GF(2m)

JIANG An-you, ZHU Jin-kang   

  1. PCN and SS Laboratory, Department of Electronics Engineering and Science Information, University of Science and Technology of China, Hefei 230027, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-04-30
  • Contact: JIANG An-you

摘要:

This article proposes a novel nonlinear network code in the GF(2m) finite field. Different from previous linear network codes that linearly mix multiple input flows, the proposed nonlinear network code mixes input flows through both multiplication and exponentiation in the GF(2m). Three relevant rules for selecting proper parameters for the proposed nonlinear network code are discussed, and the relationship between the power parameter and the coding coefficient K is explored. Further analysis shows that the proposed nonlinear network code is equivalent to a linear network code with deterministic coefficients.

关键词:

linear;network;code,;network;information;flow,;nonlinear;network;code

Abstract:

This article proposes a novel nonlinear network code in the GF(2m) finite field. Different from previous linear network codes that linearly mix multiple input flows, the proposed nonlinear network code mixes input flows through both multiplication and exponentiation in the GF(2m). Three relevant rules for selecting proper parameters for the proposed nonlinear network code are discussed, and the relationship between the power parameter and the coding coefficient K is explored. Further analysis shows that the proposed nonlinear network code is equivalent to a linear network code with deterministic coefficients.

Key words:

linear network code;network information flow;nonlinear network code