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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
Rate Splitting Multiple Access for Semi-Grant-Free Transm...
Hongwu Liu, Theodoros A. Tsiftsis, Bruno Clerckx, Kyeong Jin Kim · 2021-10-05 · via cs.IT updates on arXiv.org

Enabled by hybrid grant-based (GB) and grant-free (GF) transmission techniques, GF users of internet of things (IoT) devices and massive machine-type communications (mMTC) meet opportunities to share wireless resources with GB users. In this paper, we propose a rate splitting multiple access (RSMA) strategy for an emerging semi-grant-free (SGF) transmission system to increase connectivity and reliability. In the proposed RSMA assisted SGF (RSMA-SGF) scheme, the GF users apply the rate splitting principle to realize distributed contentions and utilize transmit power most effectively for robust transmissions, meanwhile keeping themselves transparent to the GB user. Compared to existing non-orthogonal multiple access (NOMA) assisted SGF schemes, the RSMA-SGF scheme significantly decreases outage probability and achieves full multiuser diversity gain without restricting the GB and GF users' target rates to a limited value region. Exact expressions and asymptotic analysis for the outage probability are provided to facilitate the system performance evaluation of the proposed RSMA-SGF scheme. Computer simulation results clarify the superior outage performance of the RSMA-SGF scheme and verify the accuracy of the developed analytical results.