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

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
Jina AI
Jina AI
博客园 - 司徒正美
大猫的无限游戏
大猫的无限游戏
博客园 - 三生石上(FineUI控件)
J
Java Code Geeks
博客园 - 聂微东
酷 壳 – CoolShell
酷 壳 – CoolShell
爱范儿
爱范儿
美团技术团队
腾讯CDC
博客园 - Franky
MyScale Blog
MyScale Blog
人人都是产品经理
人人都是产品经理
罗磊的独立博客
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
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
月光博客
月光博客
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
aimingoo的专栏
aimingoo的专栏
博客园_首页
V
V2EX
Martin Fowler
Martin Fowler
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
Cooperative Sensing and Communication for ISAC Networks: ...
Kaitao Meng, Christos Masouros · 2024-03-29 · via cs.IT updates on arXiv.org

In this work, we study integrated sensing and communication (ISAC) networks intending to effectively balance sensing and communication (S&C) performance at the network level. Through the simultaneous utilization of multi-point (CoMP) coordinated joint transmission and distributed multiple-input multiple-output (MIMO) radar techniques, we propose a cooperative networked ISAC scheme to enhance both S&C services. Then, the tool of stochastic geometry is exploited to capture the S&C performance, which allows us to illuminate key cooperative dependencies in the ISAC network. Remarkably, the derived expression of the Cramer-Rao lower bound (CRLB) of the localization accuracy unveils a significant finding: Deploying $N$ ISAC transceivers yields an enhanced sensing performance across the entire network, in accordance with the $\ln^2N$ scaling law. Simulation results demonstrate that compared to the time-sharing scheme, the proposed cooperative ISAC scheme can effectively improve the average data rate and reduce the CRLB.