惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Last Week in AI
Last Week in AI
U
Unit 42
博客园 - 【当耐特】
Y
Y Combinator Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Microsoft Security Blog
Microsoft Security Blog
Recent Announcements
Recent Announcements
P
Proofpoint News Feed
Martin Fowler
Martin Fowler
量子位
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
有赞技术团队
有赞技术团队
aimingoo的专栏
aimingoo的专栏
博客园 - 司徒正美
美团技术团队
雷峰网
雷峰网
小众软件
小众软件
G
Google Developers Blog
GbyAI
GbyAI
Jina AI
Jina AI
爱范儿
爱范儿
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
F
Fortinet All Blogs
Vercel News
Vercel News

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
Content-Aware RSMA-Enabled Pinching-Antenna Systems for L...
Yu Hua, Yaru Fu, Yalin Liu, Zheng Shi, Kevin Hung · 2025-12-19 · via eess.SP updates on arXiv.org

The Pinching Antenna System (PAS) has emerged as a promising technology to dynamically reconfigure wireless propagation environments in 6G networks. By activating radiating elements at arbitrary positions along a dielectric waveguide, PAS can establish strong line-of-sight (LoS) links with users, significantly enhancing channel gain and deployment flexibility, particularly in high-frequency bands susceptible to severe path loss. To further improve multi-user performance, this paper introduces a novel content-aware transmission framework that integrates PAS with rate-splitting multiple access (RSMA). Unlike conventional RSMA, the proposed RSMA scheme enables users requesting the same content to share a unified private stream, thereby mitigating inter-user interference and reducing power fragmentation. We formulate a joint optimization problem aimed at minimizing the average system latency by dynamically adapting both antenna positioning and RSMA parameters according to channel conditions and user requests. A Content-Aware RSMA and Pinching-antenna Joint Optimization (CARP-JO) algorithm is developed, which decomposes the non-convex problem into tractable subproblems solved via bisection search, convex programming, and golden-section search. Simulation results demonstrate that the proposed CARP-JO scheme consistently outperforms Traditional RSMA, NOMA, and Fixed-antenna systems across diverse network scenarios in terms of latency, underscoring the effectiveness of co-designing physical-layer reconfigurability with intelligent communication strategies.