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

量子位
博客园_首页
罗磊的独立博客
云风的 BLOG
云风的 BLOG
J
Java Code Geeks
Last Week in AI
Last Week in AI
D
DataBreaches.Net
Jina AI
Jina AI
博客园 - Franky
大猫的无限游戏
大猫的无限游戏
Apple Machine Learning Research
Apple Machine Learning Research
V
V2EX
D
Docker
MongoDB | Blog
MongoDB | Blog
B
Blog RSS Feed
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
宝玉的分享
宝玉的分享
Engineering at Meta
Engineering at Meta
The Cloudflare Blog
博客园 - 三生石上(FineUI控件)
有赞技术团队
有赞技术团队
人人都是产品经理
人人都是产品经理
H
Help Net Security
T
The Blog of Author Tim Ferriss

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
Enhancing Non-Orthogonal Multiple Access By Forming Relay...
Jungho So, Youngchul Sung · 2015-10-26 · via cs.IT updates on arXiv.org

In this paper, using relaying broadcast channels (RBCs) as component channels for non-orthogonal multiple access (NOMA) is proposed to enhance the performance of NOMA in single-input single-output (SISO) cellular downlink systems. To analyze the performance of the proposed scheme, an achievable rate region of a RBC with compress-and-forward (CF) relaying is newly derived based on the recent work of noisy network coding (NNC). Based on the analysis of the achievable rate region of a RBC with decode-and-forward (DF) relaying, CF relaying, or CF relaying with dirty-paper coding (DPC) at the transmitter, the overall system performance of NOMA equipped with RBC component channels is investigated. It is shown that NOMA with RBC-DF yields marginal gain and NOMA with RBC-CF/DPC yields drastic gain over the simple NOMA based on broadcast component channels in a practical system setup. By going beyond simple broadcast channel (BC)/successive interference cancellation (SIC) to advanced multi-terminal encoding including DPC and CF/NNC, far larger gains can be obtained for NOMA.