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.
Ian goodfellow, yoshua bengio, and aaron courville: Deep learning: The mit press, 2016, 800 pp, isbn: 0262035618
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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.