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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
Fast-Forward Relaying Scheme to Mitigate Jamming Attacks ...
Vivek Chaudhary, J. Harshan · 2020-04-20 · via cs.IT updates on arXiv.org

In this work, we address reliable communication of low-latency packets in the presence of a full-duplex adversary that is capable of executing a jamming attack while also being able to measure the power levels on various frequency bands. Due to the presence of a strong adversary, first, we point out that traditional frequency-hopping does not help since unused frequency bands may not be available, and moreover, the victim's transition between the frequency bands would be detected by the full-duplex adversary. Identifying these challenges, we propose a new cooperative mitigation strategy, referred to as the Semi-Coherent Fast-Forward Full-Duplex (SC-FFFD) relaying technique, wherein the victim node, upon switching to a new frequency band, seeks the assistance of its incumbent user, which is also a full-duplex radio, to instantaneously forward its messages to the destination using a portion of their powers. Meanwhile, the two nodes cooperatively use their residual powers on the jammed frequency band so as to engage the adversary to continue executing the jamming attack on the same band. Using on-off keying (OOK) and phase-shift-keying (PSK) as the modulation schemes at the victim and the helper node, respectively, we derive upper bounds on the probability of error of jointly decoding the information symbols of the two nodes, and subsequently derive analytical solutions to arrive at the power-splitting factor between the two frequency bands to minimize the error of both the nodes. We also present extensive simulation results for various signal-to-noise-ratio values and PSK constellations to showcase the efficacy of the proposed approach.