Space-time design for deep joint source channel coding of images Over MIMO channels
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Abstract (arXiv)
We propose novel deep joint source-channel coding (DeepJSCC) algorithms for wireless image transmission over multi-input multi-output (MIMO) Rayleigh fading channels, when channel state information (CSI) is available only at the receiver. We consider two different schemes; one exploiting the spatial diversity and the other exploiting the spatial multiplexing gain of the MIMO channel, respectively. For the former, we utilize an orthogonal space-time block code (OSTBC) to achieve full diversity and increase the robustness against channel variations. In the latter, we directly map the input to the antennas, where the additional degree of freedom can be used to send more information about the source signal. Simulation results show that the diversity scheme outperforms the multiplexing scheme for lower signal-to-noise ratio (SNR) values and a smaller number of receive antennas at the AP. When the number of transmit antennas is greater than two, however, the full-diversity scheme becomes less beneficial. We also show that both the diversity and multiplexing schemes can achieve comparable performance with the state-of-the-art BPG algorithm delivered at the instantaneous capacity of the MIMO channel, which serves as an upper bound on the performance of separation-based practical systems.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Oct 2022.
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Citing papers per year: 2024: 3; 2025: 1; 2026: 1.
5 papers.
- 2024Joint Source-Channel Coding: Fundamentals and Recent Progress in Practical Designscited by 32
- 2024Diffusion-Aided Joint Source Channel Coding For High Realism Wireless Image Transmissioncited by 11
- 2024Deep Learning in Physical Layer: Review on Data Driven End-to-End Communication Systems and their Enabling Semantic Applicationscited by 6
- 2025Semantic Channel Equalization Strategies for Deep Joint Source-Channel Codingcited by 2
- 2026Restoration Flow Matching-Based Channel Refinement and Equalization Correction for MIMO Semantic Communicationscited by 0
- 2026Restoration Flow Matching-Based Channel Refinement and Equalization Correction for MIMO Semantic Communications26 Jul 2026
- 2025Semantic Channel Equalization Strategies for Deep Joint Source-Channel Coding6 Oct 2025
- 2024Joint Source-Channel Coding: Fundamentals and Recent Progress in Practical Designs26 Sep 2024
- 2024Diffusion-Aided Joint Source Channel Coding For High Realism Wireless Image Transmission27 Apr 2024
- 2024Deep Learning in Physical Layer: Review on Data Driven End-to-End Communication Systems and their Enabling Semantic Applications8 Jan 2024