Advanced Wireless Communication Techniques

Últimos artículos

• AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air

  Shiyi Yang, Xiaoxue Yu, Rongpeng Li, Jianhang Zhu, Zhifeng Zhao, Honggang Zhang · 28 de agosto de 2026

  Operating Large Language Models (LLMs) on edge devices is increasingly challenged by limited communication bandwidth and strained computational and memory costs. Thus, cloud-assisted remote fine-tuning becomes indispensable. Nevertheless, existing Low-Rank Adaptation (LoRA) approaches typically empl…

• Context-Aware Markov VAE for CSI Compression in Wireless Systems

  Efstathios Chatziloizos, Konstantinos Vandikas, Aneta Vulgarakis Feljan, Zheng Chen, Nikolaos Pappas · 16 de junio de 2026

  This paper considers neural channel state information (CSI) compression for time-varying massive multiple-input multiple-output (MIMO) channels in frequency division duplex (FDD) systems with limited feedback resources. The main challenge lies in obtaining a compact and efficient representation of t…

• Rethinking Beam Management: Generalization Limits Under Hardware Heterogeneity

  Nikita Zeulin, Olga Galinina, Ibrahim Kilinc, Sergey Andreev, Robert W. Heath Jr · 23 de febrero de 2026

  Hardware heterogeneity across diverse user devices poses new challenges for beam-based communication in 5G and beyond. This heterogeneity limits the applicability of machine learning (ML)-based algorithms. This article highlights the critical need to treat hardware heterogeneity as a first-class des…

• Machine Learning Decoder for 5G NR PUCCH Format 0

  Anil Kumar Yerrapragada, Jeeva Keshav S, Ankit Gautam, Radha Krishna Ganti · 21 de enero de 2026

  5G cellular systems depend on the timely exchange of feedback control information between the user equipment and the base station. Proper decoding of this control information is necessary to set up and sustain high throughput radio links. This paper makes the first attempt at using Machine Learning …

• Generalization Bounds for Transformer Channel Decoders

  Qinshan Zhang, Bin Chen, Yong Jiang, Shu-Tao Xia · 13 de enero de 2026

  Transformer channel decoders, such as the Error Correction Code Transformer (ECCT), have shown strong empirical performance in channel decoding, yet their generalization behavior remains theoretically unclear. This paper studies the generalization performance of ECCT from a learning-theoretic perspe…

• Phase-Aware Code-Aided EM Algorithm for Blind Channel Estimation in PSK-Modulated OFDM

  Chin-Hung Chen, Ivana Nikoloska, Wim van Houtum, Yan Wu, Alex Alvarado · 27 de noviembre de 2025

  This paper presents a fully blind phase-aware expectation-maximization (EM) algorithm for OFDM systems with the phase-shift keying (PSK) modulation. We address the well-known local maximum problem of the EM algorithm for blind channel estimation. This is primarily caused by the unknown phase ambigui…

• Flow matching-based generative models for MIMO channel estimation

  Wenkai Liu, Nan Ma, Jianqiao Chen, Xiaoxuan Qi, Yuhang Ma · 17 de noviembre de 2025

  Diffusion model (DM)-based channel estimation, which generates channel samples via a posteriori sampling stepwise with denoising process, has shown potential in high-precision channel state information (CSI) acquisition. However, slow sampling speed is an essential challenge for recent developed DM-…