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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
Uplink Performance of Conventional and Massive MIMO Cellu...
Anastasios K. Papazafeiropoulos, Hien Quoc Ngo, Tharm Ratnarajah · 2015-04-10 · via cs.IT updates on arXiv.org

Massive multiple-input multiple-output (MIMO) networks, where the base stations (BSs) are equipped with large number of antennas and serve a number of users simultaneously, are very promising, but suffer from pilot contamination. Despite its importance, delayed channel state information (CSI) due to user mobility, being another degrading factor, lacks investigation in the literature. Hence, we consider an uplink model, where each BS applies zero-forcing decoder, accounting for both effects, but with the focal point on the relative users' movement with regard to the BS antennas. In this setting, analytical closed-form expressions for the sum-rate with finite number of BS antennas, and the asymptotic limits with infinite number of BS antennas epitomize the main contributions. In particular, the probability density function of the signal-to-interference-plus-noise ratio and the ergodic sum-rate are derived for any finite number of antennas. Insights of the impact of the arising Doppler shift due to user mobility into the low signal-to-noise ratio regime as well as the outage probability are obtained. Moreover, asymptotic analysis performance results in terms of infinitely increasing number of antennas, power, and both numbers of antennas and users (while their ratio is fixed) are provided. The numerical results demonstrate the performance loss in various Doppler shifts. An interesting observation is that massive MIMO is favorable even in time-varying channel conditions.