Caterpillar RLNC (CRLNC): A Practical Finite Sliding Window RLNC Approach

Simon Wunderlich, Frank Gabriel, Sreekrishna Pandi, Frank H.P. Fitzek, Martin Reisslein

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

Random linear network coding (RLNC) is a popular coding scheme for improving communication and content distribution over lossy channels. For packet streaming applications, such as video streaming and general IP packet streams, recent research has shown that sliding window RLNC approaches can reduce the in-order delay compared with block-based RLNC. However, existing sliding window RLNC approaches have prohibitive computational complexity or require feedback from the receivers to the sender. We introduce caterpillar RLNC (CRLNC), a practical finite sliding window RLNC approach that does not require feedback. CRLNC requires only simple modifications of the encoded packet structure and elementary pre-processing steps of the received coded packets before feeding the received coding coefficients and symbols into a standard block-based RLNC decoder. We demonstrate through extensive simulations that CRLNC achieves the reliability and low computational complexity of block-based RLNC, while achieving the low in-order delays of sliding window RLNC.

Original languageEnglish (US)
Article number8052109
Pages (from-to)20183-20197
Number of pages15
JournalIEEE Access
Volume5
DOIs
StatePublished - Sep 26 2017

Keywords

  • Computational complexity
  • delay
  • random linear network coding (RLNC)
  • sliding window

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

Fingerprint Dive into the research topics of 'Caterpillar RLNC (CRLNC): A Practical Finite Sliding Window RLNC Approach'. Together they form a unique fingerprint.

  • Cite this

    Wunderlich, S., Gabriel, F., Pandi, S., Fitzek, F. H. P., & Reisslein, M. (2017). Caterpillar RLNC (CRLNC): A Practical Finite Sliding Window RLNC Approach. IEEE Access, 5, 20183-20197. [8052109]. https://doi.org/10.1109/ACCESS.2017.2757241