Releases WiWorld-RealData, a multi-modal real-world dataset of dual-band CIRs aligned with images, LiDAR, mmWave radar and GNSS data, with a path-loss prediction case study showing 2.02 dB MAE.
Channel measurement, modeling, and simulation for 6G: A survey and tutorial
9 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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ChannelLM-driven digital twin architecture reduces channel prediction error by 4.23 dB in unseen environments versus small AI models while achieving 70 ms end-to-end latency.
Under equal physical aperture, 15 GHz FR3 measurements show higher spectral efficiency than 8 GHz due to more antenna elements overcoming increased sparsity, despite a 3 dB coverage deficit.
New 4.85 GHz urban double-directional channel measurements in Japan yield LSP statistics and an indicative 4–28 GHz log-log scaling model for delay and angular spreads.
Measurements indicate that delay spread stays constant in LOS but decreases in NLOS from 8 to 15 GHz, with angular spreads also decreasing, leading to slightly higher capacity at higher frequency.
Outdoor 330-360 GHz MIMO channel measurements with phase-drift-aware SAGE algorithm for improved parameter estimation and characterization of path loss, spreads, and near-field effects.
Under a dynamic generalized channel model, OFDM and DFT-s-OFDM can be tuned for superior reliability and stability compared to AFDM and OTFS, which only retain advantages in sparse stationary settings.
A Transformer-based generative model builds an environment-aware channel knowledge base that is injected into JSCC encoders and decoders, achieving 10^{-3} level channel estimation error and outperforming benchmarks in semantic communication performance.
Urban A2G measurements at FR1 and FR3 frequencies show the close-in path loss model outperforms 3GPP, NLoS increases path loss exponent and shadow fading, and higher frequencies reduce mean RMS-DS from 93.11 ns to 46.84 ns while raising mean Rician K-factor from 9.16 dB to 12.88 dB, with lognormal a
citing papers explorer
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WiWorld-RealData: A Real-World Multi-Modal Dataset for 6G Wireless World Models
Releases WiWorld-RealData, a multi-modal real-world dataset of dual-band CIRs aligned with images, LiDAR, mmWave radar and GNSS data, with a path-loss prediction case study showing 2.02 dB MAE.
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Paradigm Shift from Statistical Channel Modeling to Digital Twin Prediction: An Environment-Generalizable ChannelLM for 6G AI-enabled Air Interface
ChannelLM-driven digital twin architecture reduces channel prediction error by 4.23 dB in unseen environments versus small AI models while achieving 70 ms end-to-end latency.
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Measurement-Based Massive MIMO Channel Characterization and Performance Evaluation at FR3 (8 and 15 GHz) Under Equal Physical Aperture
Under equal physical aperture, 15 GHz FR3 measurements show higher spectral efficiency than 8 GHz due to more antenna elements overcoming increased sparsity, despite a 3 dB coverage deficit.
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Urban Macro/Microcellular Channel Characterization at 4.85~GHz With Literature-Referenced Upper-FR1-to-FR3 Cross-Band Analysis
New 4.85 GHz urban double-directional channel measurements in Japan yield LSP statistics and an indicative 4–28 GHz log-log scaling model for delay and angular spreads.
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Measurement-Based Analysis of Outdoor Massive MIMO Channel Characteristics over FR3 Frequency Band
Measurements indicate that delay spread stays constant in LOS but decreases in NLOS from 8 to 15 GHz, with angular spreads also decreasing, leading to slightly higher capacity at higher frequency.
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Channel Measurements and Characterization with Phase Drift Compensation for Outdoor 330-360 GHz MIMO Communications
Outdoor 330-360 GHz MIMO channel measurements with phase-drift-aware SAGE algorithm for improved parameter estimation and characterization of path loss, spreads, and near-field effects.
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Channel-Aware Waveform Selection Criteria Across Different Waveform Domains
Under a dynamic generalized channel model, OFDM and DFT-s-OFDM can be tuned for superior reliability and stability compared to AFDM and OTFS, which only retain advantages in sparse stationary settings.
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Generative Channel Knowledge Base With Environmental Information for Joint Source-Channel Coding in Semantic Communications
A Transformer-based generative model builds an environment-aware channel knowledge base that is injected into JSCC encoders and decoders, achieving 10^{-3} level channel estimation error and outperforming benchmarks in semantic communication performance.
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Measurement-Based Characterization and Statistical Modeling of 6G Urban Low-Altitude A2G Channels across FR1 and FR3
Urban A2G measurements at FR1 and FR3 frequencies show the close-in path loss model outperforms 3GPP, NLoS increases path loss exponent and shadow fading, and higher frequencies reduce mean RMS-DS from 93.11 ns to 46.84 ns while raising mean Rician K-factor from 9.16 dB to 12.88 dB, with lognormal a