A unified sensing-assisted framework reduces CSI acquisition overhead in flexible-antenna systems to a two-stage process of DOA sensing from uplink data followed by minimal pilot calibration of path gains, using SOC-Newton-MUSIC for LOS and FOC-Newton-MUSIC for NLOS environments.
The roadmap to 6G: AI empowered wireless networks
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
LPWTNet reconstructs statistical channel fingerprints for massive MIMO by framing the task as tensor restoration and using a Laplacian pyramid with wavelet convolutions for multi-scale efficiency.
citing papers explorer
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Sensing-Assisted Channel Estimation for Flexible-Antenna Systems: A Unified Framework
A unified sensing-assisted framework reduces CSI acquisition overhead in flexible-antenna systems to a two-stage process of DOA sensing from uplink data followed by minimal pilot calibration of path gains, using SOC-Newton-MUSIC for LOS and FOC-Newton-MUSIC for NLOS environments.
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Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework
LPWTNet reconstructs statistical channel fingerprints for massive MIMO by framing the task as tensor restoration and using a Laplacian pyramid with wavelet convolutions for multi-scale efficiency.