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

美团技术团队
人人都是产品经理
人人都是产品经理
月光博客
月光博客
V
V2EX
WordPress大学
WordPress大学
酷 壳 – CoolShell
酷 壳 – CoolShell
Last Week in AI
Last Week in AI
博客园 - 三生石上(FineUI控件)
小众软件
小众软件
Hugging Face - Blog
Hugging Face - Blog
V
Visual Studio Blog
宝玉的分享
宝玉的分享
雷峰网
雷峰网
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园 - Franky
博客园 - 聂微东
博客园 - 司徒正美
博客园 - 【当耐特】
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
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
大猫的无限游戏
大猫的无限游戏
博客园 - 叶小钗
阮一峰的网络日志
阮一峰的网络日志

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
The Two-user Causal Cognitive Interference Channel: Novel...
Martina Cardone, Daniela Tuninetti, Raymond Knopp · 2015-03-25 · via cs.IT updates on arXiv.org

This paper studies the two-user Causal Cognitive Interference Channel (CCIC), where two transmitters aim to communicate independent messages to two different receivers via a common channel. One source, referred to as the cognitive, is capable of overhearing the other source, referred to as the primary, through a noisy in-band link and thus can assist in sending the primary's data. Two novel outer bounds of the type $2R_p+R_c$ and $R_p+2R_c$ are derived for the class of injective semi-deterministic CCICs where the noises at the different source-destination pairs are independent. An achievable rate region is derived based on Gelfand-Pinsker binning, superposition coding and simultaneous decoding at the receivers. The lower and outer bounds are then specialized to the practically relevant Gaussian noise case. The authors of this paper recently characterized to within a constant gap the capacity of the symmetric Gaussian CCIC in (a) the strong interference regime, and (b) for a subset of the weak interference regime when the cooperation link is larger than a given threshold. This work characterizes to within a constant gap the capacity for the symmetric Gaussian CCIC in the regime that was still open. In particular, it is shown that the novel outer bounds are necessary to characterize the capacity to within a constant gap when the cooperation link is weaker than the direct links, that is, in this regime unilateral cooperation leaves some system resources underutilized.