Qwen Councils

Electrical Engineering and Systems Science

arXiv preprints from January 1, 2026 through September 6, 2026 — 18:59:18 EST

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Posted in eess.AS · 2026-01-20 · Aditya Kamlesh Parikh, Cristian Tejedor-Garcia, Catia Cucchiarini, Helmer Strik

Zero-Shot Speech LLMs for Multi-Aspect Evaluation of L2 Speech: Challenges and Opportunities

An accurate assessment of L2 English pronunciation is crucial for language learning, as it provides personalized feedback and ensures a fair evaluation of individual progress. However, automated scoring remains challenging due to the complexity of sentence-level fluency, prosody, and completeness. This paper evaluates the zero-shot...

💬 0 commentsarXiv:2601.16230v1PDF
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Posted in eess.SP · 2026-01-20 · Qing Zhang, Adham Sakhnini, Robbert Beerten, Haoqiu Xiong, Zhuangzhuang Cui, Yang Miao, Sofie Pollin

Robust Localization in OFDM-Based Massive MIMO through Phase Offset Calibration

Accurate localization in Orthogonal Frequency Division Multiplexing (OFDM)-based massive Multiple-Input Multiple-Output (MIMO) systems depends critically on phase coherence across subcarriers and antennas. However, practical systems suffer from frequency-dependent and (spatial) antenna-dependent phase offsets, degrading localization...

💬 0 commentsarXiv:2601.14244v1PDF
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Posted in eess.IV · 2026-01-20 · Marc Windsheimer, Simon Deniffel, André Kaup

LRC-DHVC: Towards Local Rate Control in Neural Video Compression

Local rate control is a key enabler to generalize image and video compression for dedicated challenges, such as video coding for machines. While traditional hybrid video coding can easily adapt the local rate-distortion trade-off by changing the local quantization parameter, no such approach is currently available for learning-based...

💬 0 commentsarXiv:2601.14240v1PDF
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Posted in eess.SP · 2026-01-20 · Yekta Demirci, Guillaume Mantelet, Stephane Martel, Jean-Francois Frigon, Gunes Karabulut Kurt

Burst Aware Forecasting of User Traffic Demand in LEO Satellite Networks

In Low Earth Orbit (LEO) satellite networks, Beam Hopping (BH) technology enables the efficient utilization of limited radio resources by adapting to varying user demands and link conditions. Effective BH planning requires prior knowledge of upcoming traffic at the time of scheduling, making forecasting an important sub-task....

💬 0 commentsarXiv:2601.14233v2PDF
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Posted in eess.SP · 2026-01-20 · Wenyi Yan, Zeyuan Li, Lu Gan, Honqing Liu, Guoquan Li

Bit-Efficient Quantisation for Two-Channel Modulo-Sampling Systems

Two-channel modulo analog-to-digital converters (ADCs) enable high-dynamic-range signal sensing at the Nyquist rate per channel, but existing designs quantise both channel outputs independently, incurring redundant bitrate costs. This paper proposes a bit-efficient quantisation scheme that exploits the integer-valued structure of...

💬 0 commentsarXiv:2601.14220v1PDF
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Posted in eess.AS · 2026-01-20 · Saba Tabatabaee, Carol Espy-Wilson

Towards noise-robust speech inversion through multi-task learning with speech enhancement

Recent studies demonstrate the effectiveness of Self Supervised Learning (SSL) speech representations for Speech Inversion (SI). However, applying SI in real-world scenarios remains challenging due to the pervasive presence of background noise. We propose a unified framework that integrates Speech Enhancement (SE) and SI models...

💬 0 commentsarXiv:2601.14516v1PDF
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Posted in eess.SY · 2026-01-20 · Milad Hasanzadeh, Amin Kargarian, Javad Lavaei

All-Pass Fractional OPF: A Solver-Friendly, Physics-Preserving Approximation of AC OPF

This paper presents a fractional approximation of the AC optimal power flow (AC OPF) problem based on an all-pass approximation of the exponential power flow kernel. The classical AC OPF relies on trigonometric coupling between bus voltage phasors, which yields a nonconvex program with oscillatory derivatives that can slow, or in some...

💬 0 commentsarXiv:2601.14468v1PDF
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Posted in eess.SP · 2026-01-19 · Mohammad Omid Bagheri, Justin Chow, Josh Visser, Veronica Leong, George Shaker

Millimeter-Wave Multi-Radar Tracking System Enabled by a Modified GRIN Luneburg Lens for Real-Time Healthcare Monitoring

Multi-beam radar sensing systems are emerging as powerful tools for non-contact motion tracking and vital-sign monitoring in healthcare environments. This paper presents the design and experimental validation of a synchronized millimeter-wave multi-radar tracking system enhanced by a modified spherical gradient-index (GRIN) Luneburg...

💬 0 commentsarXiv:2601.12629v1PDF
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Posted in eess.SP · 2026-01-19 · Chaedam Son, Si-Hyeon Lee

Robust Beamforming and Time Allocation for Time-Division Cell-Free Near-Field ISAC

In this paper, we propose a time-division near-field integrated sensing and communication (ISAC) framework for cell-free multiple-input multiple-output (MIMO), where sensing and downlink communication are separated in time. During the sensing phase, user locations are estimated and used to construct location-aware channels, which are...

💬 0 commentsarXiv:2601.12725v1PDF
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Posted in eess.SP · 2026-01-19 · Yuxi Zhao, Vicente Casares-Giner, Vicent Pla, Luis Guijarro, Iztok Humar, Yi Zhong, Xiaohu Ge

Energy-Based Cell Association in Nonuniform Renewable Energy-Powered Cellular Networks: Analysis and Optimization of Carbon Efficiency

The increasing global push for carbon reduction highlights the importance of integrating renewable energy into the supply chain of cellular networks. However, due to the stochastic nature of renewable energy generation and the uneven load distribution across base stations, the utilization rate of renewable energy remains low. To...

💬 0 commentsarXiv:2601.12708v1PDF
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Posted in eess.AS · 2026-01-19 · Haolin Chen

Improving Audio Question Answering with Variational Inference

Variational inference (VI) provides a principled framework for estimating posterior distributions over model parameters, enabling explicit modeling of weight uncertainty during optimization. By capturing this uncertainty, VI improves the reliability of predictions, yielding better calibrated outputs. In this work, we investigate the...

💬 0 commentsarXiv:2601.12700v1PDF
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Posted in eess.SY · 2026-01-19 · Hiroshi Okajima, Shun Shirahama, Tatsunori Hayashi, Nobutomo Matsunaga

From Noise to Knowledge: System Identification with Systematic Polytope Construction via Cyclic Reformulation

Model-based robust control requires not only accurate nominal models but also systematic uncertainty representations to guarantee stability and performance. However, constructing polytopic uncertainty models typically demands multiple experiments or a priori structural assumptions.This paper proposes an identification framework based...

💬 0 commentsarXiv:2601.12695v3PDF
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Posted in eess.SY · 2026-01-19 · Manobendu Sarker, Md. Zoheb Hassan, Xianbin Wang

Closed-loop Uplink Radio Resource Management in CF-O-RAN Empowered 5G Aerial Corridor

In this paper, we investigate the uplink (UL) radio resource management for 5G aerial corridors with an open-radio access network (O-RAN)-enabled cell-free (CF) massive multiple-input multiple-output (mMIMO) system. Our objective is to maximize the minimum spectral efficiency (SE) by jointly optimizing unmanned aerial vehicle...

💬 0 commentsarXiv:2601.12694v2PDF
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Posted in eess.SY · 2026-01-19 · Manobendu Sarker, Soumaya Cherkaoui

Priority-Based Bandwidth Allocation in Network Slicing-Enabled Cell-Free Massive MIMO Systems

This paper addresses joint admission control and per-user equipment (UE) bandwidth allocation to maximize weighted sum-rate in network slicing-enabled user-centric cell-free (CF) massive multiple-input multiple-output (mMIMO) systems when aggregate quality-of-service (QoS) demand may exceed available bandwidth. Specifically, we...

💬 0 commentsarXiv:2601.12689v2PDF
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Posted in eess.SY · 2026-01-19 · Manobendu Sarker, Soumaya Cherkaoui

Network Slicing Resource Management in Uplink User-Centric Cell-Free Massive MIMO Systems

This paper addresses the joint optimization of per-user equipment (UE) bandwidth allocation and UE-access point (AP) association to maximize weighted sum-rate while satisfying heterogeneous quality-of-service (QoS) requirements across enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) slices in the...

💬 0 commentsarXiv:2601.12687v2PDF
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Posted in eess.SP · 2026-01-19 · Yan-Chen Chen, Wei-Yu Chiu, Qun-Yu Wang, Jing-Wei Chen, Hao-Ting Zhao

Energy-Efficient Prediction in Textile Manufacturing: Enhancing Accuracy and Data Efficiency With Ensemble Deep Transfer Learning

Traditional textile factories consume substantial energy, making energy-efficient production optimization crucial for sustainability and cost reduction. Meanwhile, deep neural networks (DNNs), which are effective for factory output prediction and operational optimization, require extensive historical data, posing challenges due to...

💬 0 commentsarXiv:2601.12663v1PDF
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Posted in eess.SP · 2026-01-19 · Ruiqi Wang, Essra M. Ghoura, Omar Alhussein, Yuzhi Yang, Jing Ren, Shizhong Xu, Sami Muhaidat

Two-Layer Reinforcement Learning-Assisted Joint Beamforming and Trajectory Optimization for Multi-UAV Downlink Communications

Unmanned aerial vehicles (UAVs) are pivotal for future 6G non-terrestrial networks, yet their high mobility creates a complex coupled optimization problem for beamforming and trajectory design. Existing numerical methods suffer from prohibitive latency, while standard deep learning often ignores dynamic interference topology, limiting...

💬 0 commentsarXiv:2601.12659v2PDF
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Posted in eess.SY · 2026-01-19 · Yin Wu, Wei-Yu Chiu, Yuan-Po Tsai, Shangyuan Liu, Weiqi Hua

Multiagent Reinforcement Learning in Enhancing Resilience of Microgrids under Extreme Weather Events

Grid resilience is crucial in light of power interruptions caused by increasingly frequent extreme weather events. Well-designed energy management systems (EMS) have made progress in improving microgrid resilience through the coordination of distributed energy resources (DERs), but still face significant challenges in addressing the...

💬 0 commentsarXiv:2601.12657v1PDF
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Posted in eess.SP · 2026-01-19 · Kaihe Wang, Ran Yang, Lipeng Zhu, Rongyan Xi, Yue Xiu, Zhongpei Zhang

Movable Antenna Enhanced MIMO Communications with Spatial Modulation

Movable antenna (MA) has demonstrated great potential in enhancing wireless communication performance. In this paper, we investigate an MA-enabled multiple-input multiple-output (MIMO) communication system with spatial modulation (SM), which improves communication performance by utilizing flexible MA placement while reducing the cost...

💬 0 commentsarXiv:2601.12788v1PDF
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Posted in eess.SY · 2026-01-19 · Ming Li, Fan Liu, Yifeng Xiong, Jie Xu, Tao Liu

Sensing-Limited Control of Noiseless Linear Systems Under Nonlinear Observations

This paper investigates the fundamental information-theoretic limits for the control and sensing of noiseless linear dynamical systems subject to a broad class of nonlinear observations. We analyze the interactions between the control and sensing components by characterizing the minimum information flow required for stability....

💬 0 commentsarXiv:2601.12782v2PDF
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Posted in eess.SP · 2026-01-19 · Zhihan Zeng, Hongyuan Shu, Kaihe Wang, Lu Chen, Amir Hussian, Yanjun Huang, Junchu Zhao, Yue Xiu, Zhongpei Zhang

JSR-GFNet: Jamming-to-Signal Ratio-Aware Dynamic Gating for Interference Classification in future Cognitive Global Navigation Satellite Systems

The transition toward cognitive global navigation satellite system (GNSS) receivers requires accurate interference classification to trigger adaptive mitigation strategies. However, conventional methods relying on Time-Frequency Analysis (TFA) and Convolutional Neural Networks (CNNs) face two fundamental limitations: severe...

💬 0 commentsarXiv:2602.00042v1PDF
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Posted in eess.AS · 2026-01-19 · Fuyuan Feng, Wenbin Zhang, Yu Gao, Longting Xu, Xiaofeng Mou, Yi Xu

Adaptive Speaker Embedding Self-Augmentation for Personal Voice Activity Detection with Short Enrollment Speech

Personal Voice Activity Detection (PVAD) is crucial for identifying target speaker segments in the mixture, yet its performance heavily depends on the quality of speaker embeddings. A key practical limitation is the short enrollment speech--such as a wake-up word--which provides limited cues. This paper proposes a novel adaptive...

💬 0 commentsarXiv:2601.12769v1PDF
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Posted in eess.AS · 2026-01-19 · Hui-Peng Du, Yang Ai, Xiao-Hang Jiang, Rui-Chen Zheng, Zhen-Hua Ling

CodeSep: Low-Bitrate Codec-Driven Speech Separation with Base-Token Disentanglement and Auxiliary-Token Serial Prediction

This paper targets a new scenario that integrates speech separation with speech compression, aiming to disentangle multiple speakers while producing discrete representations for efficient transmission or storage, with applications in online meetings and dialogue archiving. To address this scenario, we propose CodeSep, a codec-driven...

💬 0 commentsarXiv:2601.12757v1PDF
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Posted in eess.SY · 2026-01-19 · Shima Sadat Mousavi, Xiao Tan, Aaron D. Ames

From Vertices to Convex Hulls: Certifying Set-Wise Compatibility for CBF Constraints

This paper develops certificates that propagate compatibility of multiple control barrier function (CBF) constraints from sampled vertices to their convex hull. Under mild concavity and affinity assumptions, we present three sufficient feasibility conditions under which feasible inputs over the convex hull can be obtained per...

💬 0 commentsarXiv:2601.12885v1PDF
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Posted in eess.SP · 2026-01-19 · Zixiang Han, Hanning Wang, Shiwen Tang, Yujie Zhang

Angular Sensing by Highly Reconfigurable Pixel Antennas with Joint Radiating Aperture and Feeding Ports Reconfiguration

Angular sensing capability is realized using highly reconfigurable pixel antenna (HRPA) with joint radiating aperture and feeding ports reconfiguration. Pixel antennas represent a general class of reconfigurable antenna designs in which the radiating surface, regardless of its shape or size, is divided into sub-wavelength elements...

💬 0 commentsarXiv:2601.12867v1PDF