Publication2025
Adaptive OTFS Modulation for Multi-Domain Networks Using Dynamic Neural Networks
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 2025 IEEE 2nd International Conference on Electronics Communications and Intelligent Science Ecis 2025 Proceeding
- Published
- 1 January 2025
- DOI
- 10.1109/ecis65594.2025.11086648
- Scopus ID
- 105013620119
- Authors
- 6
- Open access
- No
- Citations
- 2
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Adaptive orthogonal time frequency space modulation with deep neural networks advances wireless communication technology for next-generation networks.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3.2 Digital technology and artificial intelligence
Advanced digital communication technology development supports innovation in wireless systems.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Adaptive OTFS Modulation for Multi-Domain Networks Using Dynamic Neural Networks”. Kortex.