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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 Synergistic Gains of Coded Caching and Delayed Feedback
Jingjing Zhang, Petros Elia · 2016-04-22 · via cs.IT updates on arXiv.org

In this paper, we consider the $K$-user cache-aided wireless MISO broadcast channel (BC) with random fading and delayed CSIT, and identify the optimal cache-aided degrees-of-freedom (DoF) performance within a factor of 4. The achieved performance is due to a scheme that combines basic coded-caching with MAT-type schemes, and which efficiently exploits the prospective-hindsight similarities between these two methods. This delivers a powerful synergy between coded caching and delayed feedback, in the sense that the total synergistic DoF-gain can be much larger than the sum of the individual gains from delayed CSIT and from coded caching. The derived performance interestingly reveals --- for the first time --- substantial DoF gains from coded caching, even when the (normalized) cache size $γ$ (fraction of the library stored at each receiving device) is very small. Specifically, a microscopic $γ\approx e^{-G}$ can come within a factor of $G$ from the interference-free optimal. For example, storing at each device only a \emph{thousandth} of what is deemed as `popular' content ($γ\approx 10^{-3}$), we approach the interference-free optimal within a factor of $ln(10^3) \approx 7$ (per user DoF of $1/7$), for any number of users. This result carries an additional practical ramification as it reveals how to use coded caching to essentially buffer CSI, thus partially ameliorating the burden of having to acquire real-time CSIT.