惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

G
Google Developers Blog
人人都是产品经理
人人都是产品经理
腾讯CDC
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
WordPress大学
WordPress大学
S
SegmentFault 最新的问题
小众软件
小众软件
B
Blog
博客园 - 叶小钗
Microsoft Azure Blog
Microsoft Azure Blog
Apple Machine Learning Research
Apple Machine Learning Research
A
About on SuperTechFans
J
Java Code Geeks
Blog — PlanetScale
Blog — PlanetScale
博客园 - 司徒正美
博客园 - 【当耐特】
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Recent Announcements
Recent Announcements
宝玉的分享
宝玉的分享
Martin Fowler
Martin Fowler
Hugging Face - Blog
Hugging Face - Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Last Week in AI
Last Week in AI
V
V2EX

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
On the Downlink Performance of RSMA-based UAV Communications
Wael Jaafar, Shimaa Naser, Sami Muhaidat, Paschalis C. Sofotasio · 2020-11-10 · via cs.IT updates on arXiv.org

The use of unmanned aerial vehicles (UAVs) as base stations (BSs) is envisaged as a key enabler for the fifth generation (5G) and beyond-5G networks. Specifically, aerial base stations (UAV-BS) are expected to provide ubiquitous connectivity and high spectral efficiency. To this end, we present in this correspondence an in-depth look into the integration of rate-splitting multiple access (RSMA) with UAV-BSs and downlink transmissions. A non-convex problem of joint UAV placement, RSMA precoding, and rate splitting, aiming to maximize the weighted sum data rate of users is formulated. Due to its complexity, two sub-problems are investigated, namely the UAV placement and RSMA parameters optimization. The resulting solutions are then combined to propose a novel alternating optimization method. Simulation results illustrate the latter's efficiency compared to baseline approaches.