252 papers
This paper derives a novel exact analytical expression for the level crossing rate (LCR) of optimal single-user RIS-aided systems under blocked direct links and proposes a numerically stable approximation for direct-only channels, revealing that RIS systems effectively mitigate temporal channel variations, thereby easing the burden of channel state information acquisition.
This paper proposes a method to immerse non-polynomial Port-Hamiltonian systems into higher-dimensional polynomial representations that preserve key structural and energy properties, thereby enabling the design of stabilizing feedback laws through sum-of-squares optimization and passivity-based control.
This paper proposes a low-complexity RIS design where each user is served by a dedicated subsurface on a unique frequency band, deriving closed-form performance metrics that demonstrate optimal Line-of-Sight operation and remarkable robustness to non-Line-of-Sight conditions while significantly reducing channel estimation and processing requirements.
By analyzing real-world Californian BEV usage data to identify distinct driver profiles, this study demonstrates that Vehicle-to-Grid (V2G) adoption is most viable for "Daily Chargers" and that its impact on battery lifetime varies significantly based on calendar aging sensitivity and charging habits, ranging from increased capacity loss to potential retention improvements.
This paper introduces a novel, low-complexity Human Presence Detection system for commodity laptops that utilizes the built-in Wi-Fi hardware and a new Range-Filtered Doppler Spectrum technique to achieve privacy-preserving, calibration-free occupancy sensing without requiring external sensors or infrastructure.
This paper proposes a distributed safety-critical control framework for multi-agent systems with uncontrollable agents, utilizing a novel reconstructed Control Barrier Function based on distributed adaptive state estimates and prescribed performance parameters to decouple safety constraints and rigorously guarantee system safety.
This paper proposes an adaptive multimodal semantic transmission system for satellite communications that utilizes a dual-stream generative architecture and a large language model-based decision module to dynamically switch between audio and video streams, thereby achieving high-fidelity synchronized audiovisual reconstruction while significantly reducing bandwidth consumption under challenging channel conditions.
This paper establishes a control-theoretic framework that formalizes agentic systems as hierarchical decision authorities within feedback loops, providing a unified dynamical representation to analyze the stability, safety, and performance of AI agents that adapt controllers, strategies, and objectives in real-time.
This paper demonstrates that applying dimensional analysis and data scaling to large-scale agent-based simulations of autonomous drone swarms reveals predictable, counterintuitive scaling laws and sharp success-failure boundaries, enabling rapid, budget-aware optimization of agent counts, platform parameters, and path planning strategies across diverse mission scenarios.
This paper reveals a systematic gender bias in speech quality assessment where male listeners consistently rate audio higher than female listeners, particularly for low-quality speech, and proposes a gender-aware model that learns distinct scoring patterns to improve prediction accuracy and equity.
This paper proposes a distributed state estimation scheme for discrete-time LTI systems that utilizes the Jordan canonical form to combine local Luenberger observers with consensus-based strategies, thereby establishing necessary and sufficient conditions for asymptotic convergence while offering greater flexibility and less restrictive solvability conditions than previous work.
This paper proposes a rate-aware cell switching optimization framework for HAPS-assisted 6G networks that integrates realistic propagation losses and multi-objective formulation to significantly reduce data rate degradation while maintaining energy efficiency and user connectivity, validated through both system-level simulations and Sionna-OAI emulation.
This paper proposes and experimentally validates a flexible multi-target over-the-air emulation framework for large-scale ISAC base stations that utilizes an amplitude and phase modulation network to simulate diverse sensing targets without costly hardware, overcoming scalability challenges through optimized probe array configurations based on strictly diagonally dominant matrices.
This paper introduces Geo-ATBench, a new benchmark and the Geo-AT task that leverage geospatial semantic context to resolve acoustic ambiguities in multi-label audio tagging, demonstrating through the GeoFusion-AT framework that incorporating location-based priors significantly improves recognition performance and aligns with human judgment.
This paper proposes a path planning strategy for an autonomous underwater vehicle that fuses local conductivity-temperature-depth measurements with acoustic transmission loss data via an unscented Kalman filter to accurately estimate the sound speed profile while minimizing prediction uncertainty.
This paper introduces a layered acoustic wave (LAW) platform featuring a quasi-infinite multifunctional top layer that simultaneously suppresses acoustomigration and temperature rise, achieving a 70% reduction in heating and a record-breaking power density threshold of 45.61 dBm/mm² for high-frequency (>2 GHz) acoustic transducers.
This paper proposes a novel near-field channel estimation framework for extremely large-scale intelligent reflecting surfaces that leverages tensor modalization and harmonic analysis-inspired decoupling to create a compact distance-dependent codebook, achieving significantly higher accuracy and lower complexity than existing polar-domain methods.
The paper proposes G-STAR, an end-to-end system that integrates a time-aware speaker-tracking module with a Speech-LLM backbone to achieve robust, timestamped speaker-attributed recognition for long-form, overlapping multi-party speech while maintaining global identity consistency.
This paper proposes a 3D spectrum awareness framework for Radio Dynamic Zones that leverages matrix completion to outperform ordinary Kriging in dense measurement scenarios while demonstrating the superiority of simple and trans-Gaussian Kriging in sparse conditions, alongside the benefits of integrating multi-altitude data for improved prediction accuracy.
This paper introduces Spyglass, a cost-effective spectrum sensor that utilizes a switched array and the Searchlite protocol to achieve single-shot, multi-channel Angle of Arrival (AoA) estimation with high accuracy in dense wireless environments.