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

OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
博客园 - Franky
T
Tailwind CSS Blog
Microsoft Azure Blog
Microsoft Azure Blog
The Cloudflare Blog
博客园 - 叶小钗
N
Netflix TechBlog - Medium
罗磊的独立博客
量子位
MyScale Blog
MyScale Blog
A
About on SuperTechFans
Blog — PlanetScale
Blog — PlanetScale
V
Visual Studio Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
GbyAI
GbyAI
B
Blog
腾讯CDC
爱范儿
爱范儿
Recent Announcements
Recent Announcements
有赞技术团队
有赞技术团队
F
Fortinet All Blogs
雷峰网
雷峰网
G
Google Developers Blog
Google DeepMind News
Google DeepMind News

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
Optimal Fairness Scheduling for Coded Caching in Multi-AP...
Kagan Akcay, MohammadJavad Salehi, Giuseppe Caire · 2023-04-26 · via cs.IT updates on arXiv.org

Coded caching (CC) schemes exploit the cumulative cache memory of the users and simple linear coding to turn unicast traffic (individual file requests) into a multicast transmission. For the originally proposed $K$-user single-server/single shared link network model, CC yields an $O(K)$ gain with respect to conventional uncoded caching with the same per-user memory. While several information-theoretic optimality results for a variety of problems and carefully crafted network topologies have been proved, the gains and suitability of CC for practical scenarios such as content streaming over existing wireless networks have not yet been fully demonstrated. In this work, we consider CC for on-demand video streaming over WLANs where multiple users are served simultaneously by multiple spatially distributed access points (AP). Users sequentially request video ``chunks". The CC scheme operates above the IP layer, leaving the underlying standard physical layer and MAC layer untouched. The cache placement is completely asynchronous and decentralized, and the users are placed at random over the network coverage area. For such a system, we consider the region of achievable long-term average delivery rate (defined as the number of video chunks delivered per unit of time) and study the per-user rate distribution under proportional fairness scheduling. We also consider reduced complexity scheduling strategies and compare them with standard state-of-the-art techniques such as conventional (uncoded) caching and collision avoidance by allocating APs on different sub-channels (i.e., frequency reuse).