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Structure-Aware Decoding Strategy for High-Order Sliding Network Coding in URLLC

  • Longjie Wang
  • , Lin Bai
  • , Rui Han*
  • , Jiaxing Wang
  • , Xin Xie
  • , Jinho Choi
  • , Wei Zhang
  • *Corresponding author for this work
  • Beihang University
  • Chongqing University of Posts and Telecommunications
  • Adelaide University
  • University of New South Wales

Research output: Contribution to journalArticlepeer-review

Abstract

Sliding network coding (SNC) has emerged as a promising solution for ultra-reliable and low-latency communication (URLLC) scenarios. The performance of SNC, particularly in terms of developing the encoding matrix and decoding strategy, is heavily influenced by the order h of the underlying Galois field, GF (2h ). In this paper, we investigate high-order SNC, where h > 1, to enhance transmission efficiency by employing a Vandermonde-based encoding matrix that ensures linear independence among coded packets. To maximize decoding efficiency, we design a structure-aware decoding strategy (SA-DS), which not only dynamically exploits the relationships between successfully decoded (SD) packets and the currently decoded (CD) packet, but also utilizes the first-packet deterministic decoding (FPDD) property of the Vandermonde matrix. Additionally, we develop a Markov chain-based performance analysis framework in terms of retransmission probability, packet error rate, and expected decoding delay. Numerical results demonstrate that in the evaluated settings, the proposed scheme outperforms several traditional schemes in the moderate-erasure region. In the lowerasure region, its advantage becomes particularly pronounced (reaching one to three orders of magnitude in both PER and retransmission probability while maintaining a comparable decoding delay), making it particularly suitable for URLLC applications.

Original languageEnglish
Pages (from-to)5314-5332
Number of pages19
JournalIEEE Transactions on Communications
Volume74
DOIs
StatePublished - 2026

Keywords

  • Markov chain
  • Network coding
  • URLLC
  • sliding window

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