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Structure-Aware Decoding Strategy for High-Order Sliding Network Coding in URLLC
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DOI：10.1109/TCOMM.2026.3666651.png)
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Abstract
En 中文
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 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$h$ </tex-math></inline-formula> of the underlying Galois field, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$GF(2^{h})$ </tex-math></inline-formula>. In this paper, we investigate high-order SNC, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$h \gt 1$ </tex-math></inline-formula>, 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 low-erasure 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.
Keywords:
Network coding
URLLC
Markov chain
sliding window
Journal
IF:
8.3
Papers:
1.2W
Citations:
3.6W
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