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

雷峰网
雷峰网
B
Blog
博客园_首页
云风的 BLOG
云风的 BLOG
S
SegmentFault 最新的问题
罗磊的独立博客
Jina AI
Jina AI
C
Check Point Blog
Martin Fowler
Martin Fowler
J
Java Code Geeks
博客园 - 司徒正美
美团技术团队
MongoDB | Blog
MongoDB | Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
大猫的无限游戏
大猫的无限游戏
有赞技术团队
有赞技术团队
U
Unit 42
Hugging Face - Blog
Hugging Face - Blog
WordPress大学
WordPress大学
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
博客园 - 叶小钗
博客园 - 三生石上(FineUI控件)
小众软件
小众软件

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
Fluid Antenna Grouping Index Modulation Design for MIMO S...
Xinghao Guo, Yin Xu, Dazhi He, Cixiao Zhang, Wenjun Zhang, Yi-ya · 2024-07-16 · via cs.IT updates on arXiv.org

Index modulation (IM) significantly enhances the spectral efficiency of fluid antennas (FAs) enabled multiple-input multiple-output (MIMO) systems, which is named FA-IM. However, due to the dense distribution of ports on the FA, the wireless channel exhibits a high spatial correlation, leading to severe performance degradation in the existing FA-IM-assisted MIMO systems. To tackle this issue, this paper proposes a novel fluid antenna grouping index modulation (FA-GIM) scheme to mitigate the high correlation between the activated ports. Specifically, considering the characteristics of the FA two-dimensional (2D) surface structure and the spatially correlated channel model in FA-assisted MIMO systems, a block grouping method is adopted, where adjacent ports are assigned to the same group. Consequently, different groups independently perform port index selection and constellation symbol mapping, with only one port being activated within each group during each transmission interval. Then, a closed-form average bit error probability (ABEP) upper bound for the proposed scheme is derived. Numerical results show that, compared to state-of-the-art schemes, the proposed FA-GIM scheme consistently achieves significant bit error rate (BER) performance gains under various conditions. The proposed scheme is both efficient and robust, enhancing the performance of FA-assisted MIMO systems.