Diffusion model-based channel estimators have shown impressive performance but suffer from high computational complexity because they rely on iterative reverse sampling. This paper proposes a sampling-free diffusion transformer (DiT) for low-complexity MIMO channel estimation, termed SF-DiT-CE. Exploiting angular-domain sparsity of MIMO channels, we train a lightweight DiT to directly predict the clean channels from their perturbed observations and noise levels. At inference, the least square (LS) estimate and estimation noise condition the DiT to recover the channel in a single forward pass, eliminating iterative sampling. Numerical results demonstrate that our method achieves superior estimation accuracy and robustness with significantly lower complexity than state-of-the-art baselines.
Sensing-Aided Channel Estimation for Near-Field MIMO ISAC Systems via Cross-Attention Transformer
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics（南京航空航天大学电子信息工程学院）；Nanjing University of Aeronautics and Astronautics（南京航空航天大学）；College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications（南京邮电大学通信与信息工程学院）；Nanjing University of Posts and Telecommunications（南京邮电大学）；National Mobile Communications Research Laboratory, Southeast University（东南大学移动通信国家重点实验室）；Southeast University（东南大学）
Soft Graph Diffusion Transformer for MIMO Detection
College of Information Science and Electronic Engineering（信息科学与电子工程学院）；Theory Lab, Central Research Institute, 2012 Labs（理论实验室、中央研究所、2012实验室）；Huawei Technologies Co., Ltd.（华为技术有限公司）
College of Information Science and Electronic Engineering, Zhejiang University（浙江大学信息与电子工程学院）；Theory Lab, Central Research Institute, 2012 Labs, Huawei Technologies Co., Ltd.（华为技术有限公司2012实验室中央研究院理论实验室）
Deep CSI Feedback for FDD Massive MIMO Systems: A Curvelet Learning Approach
School of Information and Communication Engineering, Xi’an Jiaotong University（西安交通大学信息与通信工程学院）；School of Information Science and Technology, Jinan University（暨南大学信息科学技术学院）；Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology（电磁空间认知与智能控制技术实验室）
Recurrent Transformer-Based Near- and Far-Field THz Wideband Channel Estimation for UM-MIMO
Center for Next Generation Wireless and IoT（下一代无线与物联网中心）；Skolkovo Institute of Science and Technology（斯克尔科夫科学与技术研究所）；Department of IEOR（工业工程与运营研究系）；Indian Institute of Technology Bombay（孟买印度理工学院）；Faculty of Computer and Engineering Sciences（计算机与工程科学学院）；Innopolis University（因诺波利斯大学）
CSI-GPT: Integrating Generative Pre-Trained Transformer with Federated-Tuning to Acquire Downlink Massive MIMO Channels
School of Information and Electronics, Beijing Institute of Technology（北京理工大学信息与电子学院）；King Abdulaziz University（阿卜杜勒阿齐兹国王大学）；School of Electronics and Computer Science, University of Southampton（南安普顿大学电子与计算机科学学院）；Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)（穆罕默德·本·扎耶德人工智能大学）
LinFormer: A Linear-based Lightweight Transformer Architecture For Time-Aware MIMO Channel Prediction
School of Communication and Information Engineering, Shanghai University（上海大学通信与信息工程学院）；School of Information Science and Engineering, Southeast University（东南大学信息科学与工程学院）
Sequential and Generative Models for Vehicular Distributed MIMO Channel Prediction
College of computing GVSU（GVSU计算学院）；Univ Rennes, CNRS, IETR, UMR 6164（雷恩大学，法国国家科学研究中心，IETR，UMR 6164）；Univ Lille, CNRS, IEMN, UMR 8520（里尔大学，法国国家科学研究中心，IEMN，UMR 8520）
Score-Based Conditional Flow Models for MIMO Receiver Design with Superimposed Pilots
Beijing University of Posts and Telecommunications（北京邮电大学）；China Mobile Research Institute（中国移动研究院）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；University of Kent（肯特大学）
Beam Structured Turbo Receiver for HF Skywave Massive MIMO
National Mobile Communications Research Laboratory, Southeast University（东南大学国家移动通信重点实验室）；Purple Mountain Laboratories（紫金山实验室）；Imperial College London（帝国理工学院）；University of Delaware（特拉华大学）
Joint Localization and Orientation with Triple-Beam Fingerprints in Massive MIMO-OFDM
National Mobile Communications Research Laboratory, Southeast University（东南大学国家移动通信重点实验室）；Purple Mountain Laboratories（紫金山实验室）；Department of Electrical and Computer Engineering, University of Delaware（特拉华大学电气与计算机工程系）
Generative Diffusion Model Driven Massive Random Access in Massive MIMO Systems
Beijing Institute of Technology（北京理工大学）；State Key Laboratory of CNS/ATM（通信网络与业务融合国家重点实验室）；MIIT Key Laboratory of Complex-Field Intelligent Sensing（复杂场智能感知工业和信息化部重点实验室）；Advanced Technology Research Institute, BIT（北京理工大学先进技术研究院）；Yangtze Delta Region Academy, BIT（北京理工大学长三角研究院）；Ocean University of China（中国海洋大学）；Singapore University of Technology and Design（新加坡科技设计大学）；Princeton University（普林斯顿大学）
