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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
QoS-Aware NOMA Design for Downlink Pinching-Antenna Systems
Yanqing Xu, Zhiguo Ding, Donghong Cai, Vincent W. S. Wong · 2025-04-18 · via eess.SP updates on arXiv.org

Pinching antennas, implemented by applying small dielectric particles on a waveguide, have emerged as a promising flexible-antenna technology ideal for next-generation wireless communications systems. Unlike conventional flexible-antenna systems, pinching antennas offer the advantage of creating line-of-sight links by enabling antennas to be activated on the waveguide at a location close to the user. This paper investigates a typical two-user non-orthogonal multiple access (NOMA) downlink scenario, where multiple pinching antennas are activated on a single dielectric waveguide to assist NOMA transmission. We formulate the problem of maximizing the data rate of one user subject to the quality-of-service requirement of the other user by jointly optimizing the antenna locations and power allocation coefficients. The formulated problem is nonconvex and difficult to solve due to the impact of antenna locations on large-scale path loss and two types of phase shifts, namely in-waveguide phase shifts and free space propagation phase shifts. To this end, we propose an iterative algorithm based on block coordinate descent and successive convex approximation techniques. Moreover, we consider the special case with a single pinching antenna, which is a simplified version of the multi-antenna case. Although the formulated problem is still nonconvex, by using the inherent features of the formulated problem, we derive the global optimal solution in closed-form, which offers important insights on the performance of pinching-antenna systems. Simulation results demonstrate that the pinching-antenna system significantly outperforms conventional fixed-position antenna systems, and the proposed algorithm achieves performance comparable to the computationally intensive exhaustive search based approach.