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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
Small Cell Offloading Through Cooperative Communication i...
Tao Han, Yujie Han, Xiaohu Ge, Qiang Li, Jing Zhang, Zhiquan Bai · 2016-06-13 · via cs.IT updates on arXiv.org

To meet the ever-growing demand for a higher communicating rate and better communication quality, more and more small cells are overlaid under the macro base station (MBS) tier, thus forming the heterogeneous networks. Small cells can ease the load pressure of MBS but lack of the guarantee of performance. On the other hand, cooperation draws more and more attention because of the great potential of small cell densification. Some technologies matured in wired network can also be applied to cellular networks, such as Software-defined networking (SDN). SDN helps simplify the structure of multi-tier networks. And it's more reasonable for the SDN controller to implement cell coordination. In this paper, we propose a method to offload users from MBSs through small cell cooperation in heterogeneous networks. Association probability is the main indicator of offloading. By using the tools from stochastic geometry, we then obtain the coverage probabilities when users are associated with different types of base stations (BSs). All the cell association and cooperation are conducted by the SDN controller. Then on this basis, we compare the overall coverage probabilities, achievable rate and energy efficiency with and without cooperation. Numerical results show that small cell cooperation can offload more users from MBS tier. It can also increase the system's coverage performance. As small cells become denser, cooperation can bring more gains to the energy efficiency of the network.