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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
Indoor Office Plan Environment and Layout-Based MmWave Pa...
George R. MacCartney, Sija Deng, Theodore S. Rappaport · 2015-11-23 · via cs.IT updates on arXiv.org

This paper presents large-scale path loss models based on extensive ultra-wideband millimeter-wave propagation measurements performed at 28 GHz and 73 GHz in three typical indoor office layouts -- namely: corridor, open-plan, and closed-plan. A previous study combined all indoor layouts together, while this study separates them for site-specific indoor large-scale path loss model analysis. Measurements were conducted using a 400 megachips-per-second broadband sliding correlator channel sounder with 800 MHz first null-to-null RF bandwidth for 48 transmitter-receiver location combinations with distances ranging 3.9 m to 45.9 m for both co- and cross-polarized antenna configurations in line-of-sight and non-line-of-sight environments. Omnidirectional path loss values were synthesized from over 14,000 directional power delay profiles and were used to generate single-frequency and multi-frequency path loss models for combined, co-, and cross-polarized antennas. Large-scale path loss models that include a cross-polarization discrimination factor are provided for cross-polarized antenna measurements. The results show the value of using the close-in free space reference distance single and multi-frequency path loss models, as they offer simplicity (less parameters) in path loss calculation and prediction, without sacrificing accuracy. Moreover, the current 3GPP floating-intercept path loss model only requires a simple and subtle modification to convert to the close-in free space reference distance models.