Qwen Councils

Electrical Engineering and Systems Science

arXiv preprints from January 1, 2026 through July 21, 2026 — 07:23:23 EST

0

Posted in eess.SY · 2026-01-14 · Luigi Romano, Ole Morten Aamo, Miroslav Krstić, Jan Åslund, Erik Frisk

Boundary adaptive observer design for semilinear hyperbolic rolling contact ODE-PDE systems with uncertain friction

This paper presents an adaptive observer design for semilinear hyperbolic rolling contact ODE-PDE systems with uncertain friction characteristics parameterized by a matrix of unknown coefficients appearing in the nonlinear (and possibly non-smooth) PDE source terms. Under appropriate assumptions of forward completeness and boundary...

💬 0 commentsarXiv:2601.09223v4PDF
0

Posted in eess.SP · 2026-01-14 · Ruisi He, Mi Yang, Zhengyu Zhang, Bo Ai, Zhangdui Zhong

Artificial Intelligence Empowered Channel Prediction: A New Paradigm for Propagation Channel Modeling

This paper proposes a novel paradigm centered on Artificial Intelligence (AI)-empowered propagation channel prediction to address the limitations of traditional channel modeling. We present a comprehensive framework that deeply integrates heterogeneous environmental data and physical propagation knowledge into AI models for...

💬 0 commentsarXiv:2601.09205v1PDF
0

Posted in eess.SP · 2026-01-14 · Weibo Wen, Shijian Gao, Haotian Zhang, Xiang Cheng, Liuqing Yang

WiFo-E: A Scalable Wireless Foundation Model for End-to-End FDD Precoding in Communication Networks

Accurate precoding in massive multiple-input multiple-output (MIMO) frequency-division duplexing (FDD) systems relies on efficient channel state information (CSI) acquisition. End-to-end learning frameworks improve performance by jointly optimizing this process, but they lack scalability and fail to generalize across different system...

💬 0 commentsarXiv:2601.09186v1PDF
0

Posted in eess.SP · 2026-01-14 · Haotian Zhang, Shijian Gao, Xiang Cheng

WiFo-M$^2$: Empower Wireless Communications With Plug-and-Play Environment Sensing via Foundation Model

The emerging convergence of next-generation wireless networks and agentic artificial intelligence (AI) is inspiring a new vision: embodied intelligent network entities utilize environmental sensing to refine their physical-layer (PHY) actions. Despite a growing body of preliminary work, prevailing small and task-specific AI models...

💬 0 commentsarXiv:2601.09179v2PDF
0

Posted in eess.SP · 2026-01-14 · Sojeong Park, Yeongjun Kim, Hyun Jong Yang

User-Centric Stream Sensing for Grant-Free Access: Deep Learning with Covariance Differencing

Grant-free (GF) access is essential for massive connectivity but faces collision risks due to uncoordinated transmissions. While user-side sensing can mitigate these collisions by enabling autonomous transmission decisions, conventional methods become ineffective in overloaded scenarios where active streams exceed receive antennas. To...

💬 0 commentsarXiv:2601.09168v1PDF
0

Posted in eess.SY · 2026-01-14 · Marcus Greiff, Ray Zhang, Thomas Lew, John Subosits

Dynamic Association of Semantics and Parameter Estimates by Filtering

We propose a probabilistic semantic filtering framework in which parameters of a dynamical system are inferred and associated with a closed set of semantic classes in a map. We extend existing methods to a multi-parameter setting using a posterior that tightly couples semantics with the parameter likelihoods, and propose a filter to...

💬 0 commentsarXiv:2601.09158v1PDF
0

Posted in eess.SP · 2026-01-14 · Nadav Neuberger, Simon Kollecker, Martin Kaeske

Range-Doppler-Acceleration Estimation for Fast-Moving and Accelerating Targets

A central aspect of every pulsed radar signal processor is the targets Range-Doppler estimation within a Coherent Processing Interval. Conventional methods typically rely on simplifying assumptions, such as linear target motion, narrowband operation, or constant velocity, to enable fast computation. However, these assumptions break...

💬 0 commentsarXiv:2601.09317v2PDF
0

Posted in eess.SY · 2026-01-14 · Jixiang Zhang, Han Xu, Daming Cao, Yinfei Xu, Minghao Chen, Chengyu Lin

On Discrete Age of Information of Status Updating System With General Packet Arrival Processes

Characterizing Age of Information (AoI) in status updating systems with general arrival and service processes has great significance considering that the interarrival and service time of updates can possibly be arbitrary in a real world. While expressions of average continuous AoI under G/G/1/1 queues have been derived in the paper by...

💬 0 commentsarXiv:2601.09302v1PDF
0

Posted in eess.SP · 2026-01-14 · Junseok Lee, Jihye Shin, Sangyong Lee, Chang-Jae Chun

LSR-Net: A Lightweight and Strong Robustness Network for Bearing Fault Diagnosis in Noise Environment

Rotating bearings play an important role in modern industries, but have a high probability of occurrence of defects because they operate at high speed, high load, and poor operating environments. Therefore, if a delay time occurs when a bearing is diagnosed with a defect, this may cause economic loss and loss of life. Moreover, since...

💬 0 commentsarXiv:2601.10761v1PDF
0

Posted in eess.SP · 2026-01-14 · Utku Uçak, Fariba Armandoust, Matthias Mehlhose, Daniel Schäufele, Jochen Fink, Renato L. G. Cavalcante, Sławomir Stańczak

Uplink Multi-User MIMO Implementation in OpenAirInterface

Cell-Free Multiple-Input Multiple-Output (MIMO) and Open Radio Access Network (O-RAN) have been active research topics in the wireless communication community in recent years. As an open-source software implementation of the 3rd Generation Partnership Project (3GPP) 5th Generation (5G) protocol stack, OpenAirInterface (OAI) has become...

💬 0 commentsarXiv:2601.09384v2PDF
0

Posted in eess.IV · 2026-01-14 · Siheon Joo, Hongjo Kim

An Implementation of the Crack Topology Score with Extensions

The Crack Topology Score (CTS) is a recently proposed metric that focuses on evaluating the topological correctness of crack segmentation outputs. While pixel-wise metrics such as IoU or F1-score fail to capture structural validity, CTS offers a skeleton-based matching framework to measure the preservation of connectivity. This paper...

💬 0 commentsarXiv:2601.10762v1PDF
0

Posted in eess.SY · 2026-01-14 · Haohao Shi, Huy Truong-Ba, Michael E. Cholette, Brenden Harris, Juan Montes, Tommy Chan

Semi-physical Gamma-Process Degradation Modeling and Performance-Driven Opportunistic Maintenance Optimization for LED Lighting Systems

Large-scale LED lighting systems degrade through gradual package degradation and abrupt driver outages, while acceptability is determined by spatio-temporal illuminance compliance rather than component reliability alone. This paper proposes a performance-driven, simulation-in-the-loop framework for opportunistic maintenance...

💬 0 commentsarXiv:2601.09380v1PDF
0

Posted in eess.SP · 2026-01-14 · Radim Zedka, Roman Marsalek, Marek Bobula, Arman Farhang

Unique Word Channel Estimation for Oversampled OTFS

Practical aspects of orthogonal time frequency space (OTFS), such as channel estimation and its performance in fractional delay-Doppler (DD) channels, are a lively topic in the OTFS community. Oversampling and pulse shaping are also discussed in the existing literature, but not in the context of channel estimation. To the best of our...

💬 0 commentsarXiv:2601.09364v1PDF
0

Posted in eess.SP · 2026-01-14 · Gabriele Bertoli, Kai Schroeter, Rossella Arcucci, Enrica Caporali

A Hybrid Machine Learning Framework for Improved Short-Term Peak-Flow Forecasting

Reliable river flow forecasting is an essential component of flood risk management and early warning systems. It enables improved emergency response coordination and is critical for protecting infrastructure, communities, and ecosystems from extreme hydrological events. Process-based hydrological models and purely data-driven...

💬 0 commentsarXiv:2601.09336v1PDF
0

Posted in eess.SP · 2026-01-14 · Marouan Mizmizi, Stefano Tebaldini, Umberto Spagnolini

Echo-Side Integrated Sensing and Communication via Space-Time Reconfigurable Intelligent Surfaces

This paper presents an echo-side modulation framework for integrated sensing and communication (ISAC) systems. A space-time reconfigurable intelligent surface (ST-RIS) impresses a continuous-phase modulation onto the radar echo, enabling uplink data transmission with a phase modulation of the transmitted radar-like waveform. The...

💬 0 commentsarXiv:2601.09484v1PDF
0

Posted in eess.SP · 2026-01-14 · Ying Gao, Qingqing Wu, Ziyuan Zheng, Yanze Zhu, Wen Chen, Xin Lin, Shanpu Shen

Two-Scale Spatial Deployment for Cost-Effective Wireless Networks via Cooperative IRSs and Movable Antennas

This paper proposes a two-scale spatial deployment strategy to ensure reliable coverage for multiple target areas, integrating macroscopic intelligent reflecting surfaces (IRSs) and fine-grained movable antennas (MAs). Specifically, IRSs are selectively deployed from candidate sites to shape the propagation geometry, while MAs are...

💬 0 commentsarXiv:2601.09463v1PDF
0

Posted in eess.SP · 2026-01-14 · Heedong Do, Angel Lozano

Beamforming Gain with Nonideal Phase Shifters

This research sets forth a universal framework to characterize the beamforming gain achievable with arbitrarily nonideal phase shifters. Precisely, the maximum possible shortfall relative to the gain attainable with ideal phase shifters is established. Such shortfall is shown to be fundamentally determined by the perimeter of the...

💬 0 commentsarXiv:2601.09426v1PDF
0

Posted in eess.SY · 2026-01-14 · Abhishek Kumar, José-Ramón Vidal, Jorge Martinez-Bauset, Frank Y. Li

Semi-Contention-Free Access in IoT NOMA Networks: A Reinforcement Learning Framework

The unprecedented surge of massive Internet of things (mIoT) traffic in beyond fifth generation (B5G) communication systems calls for transformative approaches for multiple access and data transmission. While classical model-based tools have been proven to be powerful and precise, an imminent trend for resource management in B5G...

💬 0 commentsarXiv:2601.09422v1PDF
0

Posted in eess.SY · 2026-01-14 · Shen Chen, Chaohou Liu, Wei Yao, Jisong Wang, Shuaipo Guo, Zeng Liu, Jinjun Liu

A Novel $αβ$-Approximation Method Based on Numerical Integration for Discretizing Continuous Systems

In this article, we propose a novel discretization method based on numerical integration for discretizing continuous systems, termed the $αβ$-approximation or Scalable Bilinear Transformation (SBT). In contrast to existing methods, the proposed method consists of two factors, i.e., shape factor ($α$) and time factor ($β$). Depending...

💬 0 commentsarXiv:2601.09549v1PDF
0

Posted in eess.SY · 2026-01-14 · Jochen Stiasny, Jochen Cremer

Residual Power Flow for Neural Solvers

The energy transition challenges operational tasks based on simulations and optimisation. These computations need to be fast and flexible as the grid is ever-expanding, and renewables' uncertainty requires a flexible operational environment. Learned approximations, proxies or surrogates -- we refer to them as Neural Solvers -- excel...

💬 0 commentsarXiv:2601.09533v1PDF
0

Posted in eess.SP · 2026-01-14 · Ismaila Salihou Adamou, Michèle Wigger

Distributed Hypothesis Testing Under A Covertness Constraint

We study distributed hypothesis testing under a covertness constraint in the non-alert situation, which requires that under the null-hypothesis an external warden be unable to detect whether communication between the sensor and the decision center is taking place. We characterize the achievable Stein exponent of this setup when the...

💬 0 commentsarXiv:2601.09837v2PDF
0

Posted in eess.SP · 2026-01-14 · Fahimeh Orvati Nia, Shima Salehi, Joshua Peeples

Evaluating GAN-LSTM for Smart Meter Anomaly Detection in Power Systems

Advanced metering infrastructure (AMI) provides high-resolution electricity consumption data that can enhance monitoring, diagnosis, and decision making in modern power distribution systems. Detecting anomalies in these time-series measurements is challenging due to nonlinear, nonstationary, and multi-scale temporal behavior across...

💬 0 commentsarXiv:2601.09701v1PDF
0

Posted in eess.SY · 2026-01-14 · Karolina Schmidt, Luis Rodrigues

Collision Avoidance for Non-Cooperative Multi-Swarm Coverage Control with Bounded Disturbance Measurements

This paper proposes a new algorithm for collision-free coverage control of multiple non-cooperating swarms in the presence of bounded disturbances. A new methodology is introduced that accounts for uncertainties in disturbance measurements. The proposed methodology is used to develop an algorithm that ensures collision-free motion in...

💬 0 commentsarXiv:2601.09917v1PDF
0

Posted in eess.AS · 2026-01-14 · Kayley Seow, Alexander Arovas, Grace Steinmetz, Emily Bick

BickGraphing: Web-Based Application for Visual Inspection of Audio Recordings

BickGraphing is a browser based research tool that enables visual inspection of acoustic recordings. The tool was built in support of visualizing crop feeding pest sounds in support of the Insect Eavesdropper project; however, it is widely applicable to all audiovisualizations in research. It allows multiple uploads of large .wav...

💬 0 commentsarXiv:2601.17014v1PDF
0

Posted in eess.SY · 2026-01-13 · Hongbing Yu, Jiyu Wang, Xiaojun Zhang, Mingsheng Zhao

Research on Mechanical Properties and Deformation-Fracture Energy Consumption Characteristics of Plateau Frozen Rocks

The exploitation of mineral resources in plateau regions is confronted with critical challenges including low blasting efficiency, excessive energy consumption,and compromised operational safety when dealing with low-temperature water-bearing frozen rock masses.This study systematically investigates the dynamic-static mechanical...

💬 0 commentsarXiv:2601.08177v1PDF