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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
Pre-Chirp-Domain Index Modulation for Affine Frequency Di...
Guangyao Liu, Tianqi Mao, Ruiqi Liu, Zhenyu Xiao · 2024-02-23 · via cs.IT updates on arXiv.org

Affine frequency division multiplexing (AFDM), tailored as a novel multicarrier technique utilizing chirp signals for high-mobility communications, exhibits marked advantages compared to traditional orthogonal frequency division multiplexing (OFDM). AFDM is based on the discrete affine Fourier transform (DAFT) with two modifiable parameters of the chirp signals, termed as the pre-chirp parameter and post-chirp parameter, respectively. These parameters can be fine-tuned to avoid overlapping channel paths with different delays or Doppler shifts, leading to performance enhancement especially for doubly dispersive channel. In this paper, we propose a novel AFDM structure with the pre-chirp index modulation (PIM) philosophy (AFDM-PIM), which can embed additional information bits into the pre-chirp parameter design for both spectral and energy efficiency enhancement. Specifically, we first demonstrate that the application of distinct pre-chirp parameters to various subcarriers in the AFDM modulation process maintains the orthogonality among these subcarriers. Then, different pre-chirp parameters are flexibly assigned to each AFDM subcarrier according to the incoming bits. By such arrangement, aside from classical phase/amplitude modulation, extra binary bits can be implicitly conveyed by the indices of selected pre-chirping parameters realizations without additional energy consumption. At the receiver, both a maximum likelihood (ML) detector and a reduced-complexity ML-minimum mean square error (ML-MMSE) detector are employed to recover the information bits. It has been shown via simulations that the proposed AFDM-PIM exhibits superior bit error rate (BER) performance compared to classical AFDM, OFDM and IM-aided OFDM algorithms.