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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
Resource Allocation in NOMA based Fog Radio Access Networks
H. Zhang, Y. Qiu, K. Long, G. K. Karagiannidis, X. Wang, A. Nall · 2018-03-15 · via cs.IT updates on arXiv.org

In the wake of growth in intelligent mobile devices and wide usage of bandwidth-hungry applications of mobile Internet, the demand of wireless data traffic and ubiquitous mobile broadband is rapidly increasing. On account of these developments, the research on fifth generation (5G) networks presents an accelerative tendency on a global scale. Edge computing draw lots of attention for reducing the time delay and improving the Quality of Service for the networks. While, fog radio access networks (F-RANs) is an emergent architecture, which takes full use of edge computing and distributed storing capabilities in edge devices. In this article, we propose an architecture of non-orthogonal multiple access (NOMA) based F-RANs, which has a strong capability of edge computing and can meet the heterogeneous requirements in 5G systems. NOMA with successive interference cancellation (SIC) is regarded as a critical multi-user access technology. In NOMA, more than one user can access the same time, code domain, and frequency resources. With assigning different power levels to multi-user and implementing SIC, multiple users detection can be achieved. In this article, we provide a description of the NOMA based F-RANs architecture, and discuss the resource allocation in that. We will focus on the power and subchannel allocation in consideration of using NOMA and the edge caching. Simulation results show that the proposed NOMA baesd F-RANs architecture and the resource management mechanisms can achieve the high net utility for the RANs.