A disco RIS in bistatic ISAC degrades communication SINR through active channel aging interference but simultaneously worsens AoD estimation accuracy while improving AoA estimation accuracy.
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Channel estimation for extremely large-scale MIMO: Far-field or near-field?
12 Pith papers cite this work. Polarity classification is still indexing.
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Derives wideband compressed-domain CRB for near-field XL-MIMO, decomposing Fisher information into dominant data-diversity gain scaling as 10 log10(Ks) dB and secondary geometric-diversity from frequency-dependent Fresnel curvature, with +27.8 dB total improvement at 28 GHz and 400 MHz bandwidth.
Develops geometry-aware uncertainty sets for eavesdropper errors and an iterative algorithm optimizing PA positions, beamforming, and AN to achieve 4.7 dB higher sum rate with better secrecy than fixed-antenna systems.
UM-MIMO OCDM enables near-field ISAC via dedicated sensing subcarriers and virtual bistatic sensing for accurate range-velocity-position estimation while aiding channel estimation.
Optimal positions for massive movable antennas in near-field channels are the roots of polynomials solving specific ODEs, with a closed-form asymptotic solution that improves spectral efficiency.
A two-stage scheme extracts the common BS-RIS channel from virtual single-antenna users then refines user-specific near-field channels via compensated polar sparse recovery and alternating least squares.
A diffusion model learns the prior for Bayesian near-field wideband XL-MIMO channel estimation and a multi-scale attention denoising network improves performance over baselines.
Mobile THz wireless links cannot achieve high bandwidths while staying in the far field without unrealistic transmit power, unlike stationary THz or sub-6 GHz/mmWave systems.
A Bayesian framework with adaptive polar-domain dictionary updates and hierarchical priors improves near-field channel estimation in XL-MIMO by capturing sparsity and non-stationarity with low overhead.
DOLG amortizes non-convex joint optimization in THz CF-ISAC systems into a graph transformer-guided distributed RL policy that balances communication and sensing performance better than baselines in simulations.
Rotatable antennas at base stations mitigate inter-cell mixed near- and far-field interference in multi-cell systems, yielding higher sum rates through closed-form analysis for single-user cells and a double-layer optimization algorithm for multi-user cells.
An unsupervised detector combining a parametric Gamma reference model with a data-learned normalizing flow achieves near-supervised monitoring performance for covert communications against a disco RIS warden.
citing papers explorer
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Bistatic Integrated Sensing and Communication in the Presence of a Disco Reconfigurable Intelligent Surface: Disruption, Enhancement, or Both?
A disco RIS in bistatic ISAC degrades communication SINR through active channel aging interference but simultaneously worsens AoD estimation accuracy while improving AoA estimation accuracy.
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Wideband Compressed-Domain Cramer-Rao Bounds for Near-Field XL-MIMO: Data and Geometric Diversity Decomposition
Derives wideband compressed-domain CRB for near-field XL-MIMO, decomposing Fisher information into dominant data-diversity gain scaling as 10 log10(Ks) dB and secondary geometric-diversity from frequency-dependent Fresnel curvature, with +27.8 dB total improvement at 28 GHz and 400 MHz bandwidth.
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Robust and Secure Blockage-Aware Pinching Antenna-assisted Wireless Communication
Develops geometry-aware uncertainty sets for eavesdropper errors and an iterative algorithm optimizing PA positions, beamforming, and AN to achieve 4.7 dB higher sum rate with better secrecy than fixed-antenna systems.
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Ultra-Massive MIMO with Orthogonal Chirp Division Multiplexing for Near-Field Sensing and Communication Integration
UM-MIMO OCDM enables near-field ISAC via dedicated sensing subcarriers and virtual bistatic sensing for accurate range-velocity-position estimation while aiding channel estimation.
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Near-Field Communication with Massive Movable Antennas: An Electrostatic Equilibrium Perspective
Optimal positions for massive movable antennas in near-field channels are the roots of polynomials solving specific ODEs, with a closed-form asymptotic solution that improves spectral efficiency.
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Near-field Channel Estimation for XL-RIS-aided mmWave MIMO Systems
A two-stage scheme extracts the common BS-RIS channel from virtual single-antenna users then refines user-specific near-field channels via compensated polar sparse recovery and alternating least squares.
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Near-Field Wideband Channel Estimation for XL-MIMO Systems via Denoising Diffusion Model
A diffusion model learns the prior for Bayesian near-field wideband XL-MIMO channel estimation and a multi-scale attention denoising network improves performance over baselines.
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User Mobility Demands Near-Field Communications in Terahertz Band Wireless Networks Beyond 6G
Mobile THz wireless links cannot achieve high bandwidths while staying in the far field without unrealistic transmit power, unlike stationary THz or sub-6 GHz/mmWave systems.
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Adaptive Structured Sparse Bayesian Learning for Near-Field Non-Stationary Channel Estimation in XL-MIMO Systems
A Bayesian framework with adaptive polar-domain dictionary updates and hierarchical priors improves near-field channel estimation in XL-MIMO by capturing sparsity and non-stationarity with low overhead.
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Distributed Optimization-Learning with Graph Transformers for Terahertz Cell-Free Integrated Sensing and Communication Systems
DOLG amortizes non-convex joint optimization in THz CF-ISAC systems into a graph transformer-guided distributed RL policy that balances communication and sensing performance better than baselines in simulations.
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Rotatable Antenna Enabled Multi-Cell Mixed Near-Field and Far-Field Communications
Rotatable antennas at base stations mitigate inter-cell mixed near- and far-field interference in multi-cell systems, yielding higher sum rates through closed-form analysis for single-user cells and a double-layer optimization algorithm for multi-user cells.
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Unsupervised Semi-Parametric Plug-in Likelihood-Ratio Detection for Covert Communications in the Presence of Disco Reconfigurable Intelligent Surfaces
An unsupervised detector combining a parametric Gamma reference model with a data-learned normalizing flow achieves near-supervised monitoring performance for covert communications against a disco RIS warden.