End-to-End Deep Learning in Wireless Communication Systems: A Tutorial Review
arXiv 2603.12289•dee7a4aa16c38f1a0ac2869fc150253d1f5215c98386602ab5622f1dea25df2e
MDS-codesRISReed-SolomonUAVadversarial-robustnessautoencoderbanditsbeamformingchannel-estimationcoding-theorycomplex-probability-measuresdeep-learningindex-modulationinformation-theorylow-altitude-communicationsmMIMOmovable-antennamutual-couplingnonconvex-optimizationphysical-layerreconfigurable-intelligent-surfacesecurity-implicationsspatial-path-IMsub-packetizationwireless-communications
Paper metadata
- arXiv ID
- 2603.12289
- Version
- Not specified by this published record
- Category
- Mathematics — Information Theory (math.IT)
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Evidence and limitations
- Source ID
- arxiv_math_it
- Record identifier
- dee7a4aa16c38f1a0ac2869fc150253d1f5215c98386602ab5622f1dea25df2e
- Enrichment time
- 2026-03-16T08:51:44Z
- AI-assisted enrichment
- Yes
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