Deep learning receivers enable reliable FTN signaling with up to 75% spectral compression via sliding-window detection while maintaining low latency and robustness to channel variations.
Backpropagating through the air: Deep learning at physical layer without channel models
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Neural Equalisers for Highly Compressed Faster-than-Nyquist Signalling: Design, Performance, Complexity and Robustness
Deep learning receivers enable reliable FTN signaling with up to 75% spectral compression via sliding-window detection while maintaining low latency and robustness to channel variations.