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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
Space-time Coded Differential Modulation for Reconfigurab...
Jiawei Qiu, Harry Leib · 2025-08-14 · via cs.IT updates on arXiv.org

Reconfigurable Intelligent Surfaces (RIS) hold the promise of improving significantly coverage, as well as spectral and energy efficiency in wireless communication systems. Techniques based on RIS form a key technology for 6G systems. An important issue in RIS technology is Channel State Information (CSI), which is much more difficult to acquire in such systems. This work introduces a Differential Space-Time Modulation (DSTM) scheme integrated with Differential Reflecting Modulation (DRM) to bypass the requirement for CSI in such systems, while providing error rate gains. The DSTM scheme is based on unitary group codes. We first consider uncoded DRM for RIS to serve as a reference point. Next we provide an overview of DSTM and outline the procedures for its integration with DRM. Furthermore, we explore the extension of both the original DRM and the coded DRM-DSTM scheme to a larger number of RIS reflecting patterns $K$, and provide tables of codes for $K= 2, 3, 4$. Encoding and decoding complexities are studied as well. Extensives simulation results over quasi-static Rayleigh fading channels confirm the effectiveness of the DRM-DSTM coded system, illustrating its advantages over uncoded DRM with proper system parameters.