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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
D2D-Aided Multi-Antenna Multicasting under Generalized CSIT
Placido Mursia, Italo Atzeni, Mari Kobayashi, David Gesbert · 2021-02-03 · via cs.IT updates on arXiv.org

Multicasting, where a base station (BS) wishes to convey the same message to several user equipments (UEs), represents a common yet highly challenging wireless scenario. In fact, guaranteeing decodability by the whole UE population proves to be a major performance bottleneck since the UEs in poor channel conditions ultimately determine the achievable rate. To overcome this issue, two-phase cooperative multicasting schemes, which use conventional multicasting in a first phase and leverage device-to-device (D2D) communications in a second phase to effectively spread the message, have been extensively studied. However, most works are limited either to the simple case of single-antenna BS or to a specific channel state information at the transmitter (CSIT) setup. This paper proposes a general two-phase framework that is applicable to the cases of perfect, statistical, and topological CSIT in the presence of multiple antennas at the BS. The proposed method exploits the precoding capabilities at the BS, which enable targeting specific UEs that can effectively serve as D2D relays towards the remaining UEs, and maximize the multicast rate under some outage constraint. Numerical results show that our schemes bring substantial gains over traditional single-phase multicasting and overcome the worst-UE bottleneck behavior in all the considered CSIT configurations.