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

大猫的无限游戏
大猫的无限游戏
J
Java Code Geeks
小众软件
小众软件
D
Docker
腾讯CDC
H
Hackread – Cybersecurity News, Data Breaches, AI and More
V
V2EX
博客园 - 叶小钗
GbyAI
GbyAI
Microsoft Azure Blog
Microsoft Azure Blog
Stack Overflow Blog
Stack Overflow Blog
B
Blog RSS Feed
酷 壳 – CoolShell
酷 壳 – CoolShell
博客园 - 【当耐特】
IT之家
IT之家
博客园 - 司徒正美
M
MIT News - Artificial intelligence
T
The Blog of Author Tim Ferriss
The GitHub Blog
The GitHub Blog
罗磊的独立博客
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
L
LangChain Blog
阮一峰的网络日志
阮一峰的网络日志
C
Check Point Blog

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
LOS-based Conjugate Beamforming and Power-Scaling Law in ...
Dian-Wu Yue, Geoffrey Ye Li · 2014-04-07 · via cs.IT updates on arXiv.org

This paper is concerned with massive-MIMO systems over Rician flat fading channels. In order to reduce the overhead to obtain full channel state information and to avoid the pilot contamination problem, by treating the scattered component as interference, we investigate a transmit and receive conjugate beamforming (BF) transmission scheme only based on the line-of-sight (LOS) component. Under Rank-1 model, we first consider a single-user system with N transmit and M receive antennas, and focus on the problem of power-scaling law when the transmit power is scaled down proportionally to 1/MN. It can be shown that as MN grows large, the scattered interference vanishes, and the ergodic achievable rate is higher than that of the corresponding BF scheme based fast fading and minimum mean-square error (MMSE) channel estimation. Then we further consider uplink and downlink single-cell scenarios where the base station (BS) has M antennas and each of K users has N antennas. When the transmit power for each user is scaled down proportionally to 1/MN, it can be shown for finite users that as M grows without bound, each user obtains finally the same rate performance as in the single-user case. Even when N grows without bound, however, there still remains inter-user LOS interference that can not be cancelled. Regarding infinite users, there exists such a power scaling law that when K and the b-th power of M go to infinity with a fixed and finite ratio for a given b in (0, 1), not only inter-user LOS interference but also fast fading effect can be cancelled, while fast fading effect can not be cancelled if b=1. Extension to multi-cells and frequency-selective channels are also discussed shortly. Moreover, numerical results indicate that spacial antenna correlation does not have serious influence on the rate performance, and the BS antennas may be allowed to be placed compactly when M is very large.