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

G
Google Developers Blog
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
WordPress大学
WordPress大学
阮一峰的网络日志
阮一峰的网络日志
V
Visual Studio Blog
雷峰网
雷峰网
博客园_首页
The Cloudflare Blog
Hugging Face - Blog
Hugging Face - Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
爱范儿
爱范儿
小众软件
小众软件
D
Docker
P
Proofpoint News Feed
B
Blog
Vercel News
Vercel News
B
Blog RSS Feed
U
Unit 42
月光博客
月光博客
The GitHub Blog
The GitHub Blog
Apple Machine Learning Research
Apple Machine Learning Research
Y
Y Combinator Blog
I
InfoQ
Recent Announcements
Recent Announcements

cs.IT updates on arXiv.org

Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Sensing-Aided Secure Multicast in Rotatable Antenna-Enabl...
[Submitted on 9 May 2026 (v1), last revised 13 Sep 2026 (this ve · 2026-05-09 · via cs.IT updates on arXiv.org

View PDF HTML (experimental)

Abstract:Acquiring the channel state information (CSI) of passive eavesdroppers remains a fundamental challenge in physical layer security. The sensing capability of integrated sensing and communication (ISAC) systems enables estimation of a potential eavesdropper's angle of departure (AoD) before secure transmission. Accordingly, a sensing-aided secure multicast scheme is proposed using a rotatable antenna (RA) architecture that combines array-level and element-level rotations with analog beamforming. The scheme comprises eavesdropper sensing and secure communication stages. In the sensing stage, the maximum likelihood estimator (MLE) and corresponding Cramer--Rao bound (CRB) are derived for eavesdropper AoD estimation. The two rotation levels are then optimized through cyclic coordinate search to minimize the worst-case CRB. The resulting AoD estimate and CRB determine the center and width of the angular uncertainty region, respectively. In the communication stage, the constant-modulus analog beamformer and RA configuration are jointly optimized to maximize the worst-case secrecy rate over this region. After angular discretization and smooth approximation, the resulting problem is solved using a product-space joint optimization framework. Numerical simulation results validate the convergence and effectiveness of the proposed algorithms. It is demonstrated that i) the proposed RA-enabled sensing design effectively improves the eavesdropper AoD estimation accuracy; ii) a high and nearly constant secrecy rate is maintained over the uncertainty region; and iii) the joint optimization of the two rotation levels yields lower CRBs and higher secrecy rates than schemes employing either a fixed-position array or a single rotation level.

Submission history

From: Zequan Wang [view email]
[v1] Sat, 9 May 2026 06:04:36 UTC (315 KB)
[v2] Sun, 13 Sep 2026 14:38:39 UTC (562 KB)