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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
Event-Based Beam Tracking with Dynamic Beamwidth Adaptati...
Yasemin Karacora, Christina Chaccour, Aydin Sezgin, Walid Saad · 2022-01-18 · via cs.IT updates on arXiv.org

Terahertz (THz) communication will be a key enabler for next-generation wireless systems. While THz frequency bands provide abundant bandwidth and extremely high data rates, their effective operation is inhibited by short communication ranges and narrow beams, thus, leading to major challenges pertaining to user mobility, beam alignment, and handover. In particular, there is a strong need for novel beam tracking methods that consider the tradeoff between enhancing the received signal strength via increasing beam directivity, and increasing the coverage probability by widening the beam. In this paper, a multi-objective optimization problem is formulated with the goal of jointly maximizing the expected rate and minimizing the outage probability subject to transmit power and overhead constraints. Subsequently, a novel parameterized beamformer with dynamic beamwidth adaptation is proposed. In addition to the precoder, an event-based beam tracking approach is introduced that efficiently prevents outages caused by beam misalignment and dynamic blockage while maintaining a low pilot overhead. Simulation results show that the proposed beamforming scheme improves average rate performance and reduces the amount of outages caused by the brittle THz misalignment process and the particularly severe path loss in the THz band. Moreover, the proposed event-triggered THz channel estimation approach enables connectivity with minimal overhead and reliable communication at THz bands.