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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
Variable-Length Codes with Bursty Feedback
James Y. Chen, Recep Can Yavas, Victoria Kostina · 2023-06-24 · via cs.IT updates on arXiv.org

We study variable-length codes for point-to-point discrete memoryless channels with noiseless unlimited-rate feedback that occurs in $L$ bursts. We term such codes variable-length bursty-feedback (VLBF) codes. Unlike classical codes with feedback after each transmitted code symbol, bursty feedback fits better with protocols that employ sparse feedback after a packet is sent and also with half-duplex end devices that cannot transmit and listen to the channel at the same time. We present a novel non-asymptotic achievability bound for VLBF codes with $L$ bursts of feedback over any discrete memoryless channel. We numerically evaluate the bound over the binary symmetric channel (BSC). We perform optimization over the time instances at which feedback occurs for both our own bound and Yavas et al.'s non-asymptotic achievability bound for variable-length stop-feedback (VLSF) codes, where only a single bit is sent at each feedback instance. Our results demonstrate the advantages of richer feedback: VLBF codes significantly outperform VLSF codes at short blocklengths, especially as the error probability $ε$ decreases. Remarkably, for BSC(0.11) and error probability $10^{-10}$, our VLBF code with $L=5$ and expected decoding time $N\leq 400$ outperforms the achievability bound given by Polyanskiy et al. for VLSF codes with $L=\infty$, and our VLBF code with $L=3$.