arXiv (All)
open access
Toward Reliable and Accurate Predictive ISAC in Mobile mmWave Networks
Integrated sensing and communications (ISAC) systems offer a promising framework for beam tracking, which enhances channel awareness and improves communication reliability in mobile millimeter wave (mmWave) networks. Motivated by this, we propose a low-complexity, model-driven channel state informat
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Robust Beam Prediction for V2X Networks with Multi-Modal Sensing#997108
- Prediction-Aware Structured Resource Control for Partitioned IRS-Assisted Mobile IoT Uplinks With Semi-Blind Cascaded-Channel Acquisition#1062489
- Adaptive Predictive Sampling and Communication for Real-time Monitoring#1062384
- SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation#155213
- Learning to Focus: CSI-Free Hierarchical MARL for Reconfigurable Reflectors#986219
Record · ID 1077668
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive