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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
MIMO Precoding for Rydberg Atomic Receivers
Mingyao Cui, Qunsong Zeng, Kaibin Huang · 2024-08-26 · via cs.IT updates on arXiv.org

Leveraging the strong atom-light interaction, a Rydberg atomic receiver can measure radio waves with extreme sensitivity. Existing research primarily focuses on improving the signal detection capability of atomic receivers, while traditional signal processing schemes at the transmitter side have remained unchanged. As a result, these schemes fail to maximize the throughput of atomic receivers, given that the coupling between atomic dipole moment and radio-wave magnitude results in a nonlinear transmission model in contrast to the traditional linear one. To address this issue, our work proposes to design customized precoding techniques for atomic multiple-input-multiple-output (MIMO) systems to achieve the channel capacity. A strong-reference approximation is initially proposed to linearize the nonlinear transition model of atomic receivers. This facilitates the derivation of atomic-MIMO channel capacity as $\min(N_r/2, N_t)\log({\rm SNR})$ at high signal-to-noise ratios (SNRs) for $N_r$ receive atomic antennas and $N_t$ classic transmit antennas. Then, a new digital precoding technique, termed In-phase-and-Quadrature (IQ) aware precoding is presented, which features independent processing of I/Q data streams using four real-valued matrices. The design is shown to be capacity-achieving for the atomic MIMO system. In addition, for the case of large-scale MIMO system, we extend the preceding fully-digital precoding design to the popular hybrid precoding architecture, which cascades a classical analog precoder with a low-dimensional version of the proposed IQ-aware digital precoder. By alternatively optimizing the digital and analog parts, the hybrid design is able to approach the performance of the optimal IQ-aware fully digital precoding. Simulation results validate the superiority of proposed IQ-aware precoding methods over existing techniques in the context of atomic MIMO communication.