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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
Time-Scale-Adaptable Spectrum Sharing for Hybrid Satellit...
Yanmin Wang, Wei Feng, Yunfei Chen, Yongxu Zhu, Shidong Zhou, Ch · 2026-01-26 · via cs.IT updates on arXiv.org

Cooperation between satellite and terrestrial wireless networks promises great potential in meeting fast-growing demands for ubiquitous communications coverage. To tackle spectrum scarcity, spectrum sharing is studied for a hybrid satellite-terrestrial network where satellite links share the same group of time-slotted sub-carriers with terrestrial links opportunistically. In particular, with coarse network-wide time synchronization, a time-scale-adaptable spectrum sharing framework is proposed based on a satellite-terrestrial cooperation time scale that can be flexibly adjusted according to practical requirements. For generality, it is assumed that both full and partial frequency reuse could be adopted among the base stations (BSs) and satellite selection is supported when multiple satellites are available. Relying on only statistical channel state information (CSI), joint link scheduling and power control are explored to maximize the average sum rate of the network while ensuring quality of service (QoS) for users. To solve the complicated mixed integer programming (MIP) problem, a low-complexity spectrum sharing scheme is presented based on link-feature-sketching-aided hierarchical link clustering and Monte-Carlo-and-successive-approximation-aided transmit power optimization. Simulation results demonstrate that by link feature sketching, diversity of the links brought by the spatial distribution of the users could be well utilized. The proposed scheme promises a significant performance gain even under strict inter-link interference constraints.