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<p>This paper proposes a value-aware spatial stream allocation strategy for deep joint source-channel coding (DeepJSCC) incorporated with multiple-input multiple-output (MIMO), aimed at enhancing image transmission quality under extreme environment such as underwater scenarios. In MIMO eigenmode transmission, each stream can achieve a different diversity combining gain, with the principal stream exhibiting the highest gain. The proposed scheme allocates spatial streams of individual eigenmodes to image blocks based on their perceptual importance, which is extracted using a saliency map. Simulation results confirm that the proposed scheme achieves higher perceptual quality and structural similarity, especially in low-SNR conditions. This work demonstrates the potential of integrating semantic awareness into physical layer design, contributing to robust and efficient image communication in mission-critical applications.</p>

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Image value-based dynamic spatial stream allocation in deep joint source-channel-coded MIMO transmission for extreme environment

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月27日

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  • Shion Inokuma,
  • Goki Sawada,
  • Daisuke Hisano,
  • Kazuki Maruta

摘要

This paper proposes a value-aware spatial stream allocation strategy for deep joint source-channel coding (DeepJSCC) incorporated with multiple-input multiple-output (MIMO), aimed at enhancing image transmission quality under extreme environment such as underwater scenarios. In MIMO eigenmode transmission, each stream can achieve a different diversity combining gain, with the principal stream exhibiting the highest gain. The proposed scheme allocates spatial streams of individual eigenmodes to image blocks based on their perceptual importance, which is extracted using a saliency map. Simulation results confirm that the proposed scheme achieves higher perceptual quality and structural similarity, especially in low-SNR conditions. This work demonstrates the potential of integrating semantic awareness into physical layer design, contributing to robust and efficient image communication in mission-critical applications.