AI RESEARCH
E2E-WAVE: End-to-End Learned Waveform Generation for Underwater Video Multicasting
arXiv CS.LG
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ArXi:2604.17047v1 Announce Type: cross We present E2E-WAVE, the first end-to-end learned waveform generation system for underwater video multicasting. Acoustic channels exhibit 20--46% bit error rates where forward error correction becomes counterproductive -- LDPC increases rather than decreases errors beyond its decoding threshold. E2E-WAVE addresses this by embedding semantic similarity directly into physical layer waveforms: when decoding errors are unavoidable, the system preferentially selects semantically similar tokens rather than arbitrary corruption.