Image Value-Based Spatial Stream Allocation in MIMO Deep Joint Source-Channel Coding for Extreme Environment

This paper proposes image transmission using multiple-input multiple-output (MIMO) Deep Joint Source-Channel Coding (DeepJSCC) with focusing on value-based spatial stream allocation. DeepJSCC integrates source and channel coding through deep learning, enabling robust image transmission even under low signal-to-noise power tratio (SNR) conditions. For applications such as underwater acoustic communication, limited communication capacity due to significant SNR degradation over long distances is a challenging issue. Key proposal of this paper is to assign signal stream of MIMO eigenmode spatial division multiplexing (E-SDM) for divided image blocks according to their visibility importance. Its effectiveness is validated in terms of structural similarity index measure (SSIM) and edge preservation index (EPI) under low SNR regime.