{"total":23,"rows":[{"id":"2301.03377","title":"Machine Learning for Large-Scale Optimization in 6G Wireless Networks","created":"2023-01-03","cited_by_count":18,"area":null},{"id":"2111.07392","title":"Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges","created":"2021-11-14","cited_by_count":12,"area":null},{"id":"2303.08106","title":"Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issues","created":"2023-03-13","cited_by_count":12,"area":null},{"id":"2102.01751","title":"Distributed Conditional Generative Adversarial Networks (GANs) for Data-Driven Millimeter Wave Communications in UAV Networks","created":"2021-02-02","cited_by_count":8,"area":null},{"id":"2105.03288","title":"A Hybrid Architecture for Federated and Centralized Learning","created":"2021-05-07","cited_by_count":8,"area":null},{"id":"2102.11777","title":"Federated Learning for Physical Layer Design","created":"2021-02-23","cited_by_count":6,"area":null},{"id":"2103.00328","title":"Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamforming","created":"2021-02-27","cited_by_count":5,"area":null},{"id":"2406.03438","title":"CSI-GPT: Integrating Generative Pre-Trained Transformer with Federated-Tuning to Acquire Downlink Massive MIMO Channels","created":"2024-06-05","cited_by_count":5,"area":null},{"id":"2312.04688","title":"Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights","created":"2023-12-07","cited_by_count":4,"area":null},{"id":"2102.07450","title":"Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systems","created":"2021-02-15","cited_by_count":2,"area":null},{"id":"2105.06850","title":"Deep Learning Based RIS Channel Extrapolation with Element-grouping","created":"2021-05-14","cited_by_count":2,"area":null},{"id":"2110.07649","title":"Federated learning and next generation wireless communications: A survey on bidirectional relationship","created":"2021-10-14","cited_by_count":2,"area":null},{"id":"2110.03319","title":"Towards Federated Learning-Enabled Visible Light Communication in 6G Systems","created":"2021-10-07","cited_by_count":1,"area":null},{"id":"2503.19549","title":"Noise Resilient Over-The-Air Federated Learning In Heterogeneous Wireless Networks","created":"2025-03-25","cited_by_count":1,"area":null},{"id":"2108.07504","title":"Federated Learning with Correlated Data: Taming the Tail for Age-Optimal Industrial IoT","created":"2021-08-17","cited_by_count":0,"area":null},{"id":"2109.07729","title":"Beyond 5G RIS mmWave Systems: Where Communication and Localization Meet","created":"2021-09-16","cited_by_count":0,"area":null},{"id":"2205.03196","title":"Federated Channel Learning for Intelligent Reflecting Surfaces With Fewer Pilot Signals","created":"2022-05-06","cited_by_count":0,"area":null},{"id":"2207.06017","title":"Federated Multi-Task Learning for THz Wideband Channel and DoA Estimation","created":"2022-07-13","cited_by_count":0,"area":null},{"id":"2211.01296","title":"Machine Learning for Metasurfaces Design and Their Applications","created":"2022-11-02","cited_by_count":0,"area":null},{"id":"2308.04404","title":"Revolutionizing Wireless Networks with Federated Learning: A Comprehensive Review","created":"2023-08-01","cited_by_count":0,"area":null},{"id":"2404.03088","title":"Robust Federated Learning for Wireless Networks: A Demonstration with Channel Estimation","created":"2024-04-03","cited_by_count":0,"area":null},{"id":"2507.09627","title":"Lightweight Deep Learning-Based Channel Estimation for RIS-Aided Extremely Large-Scale MIMO Systems on Resource-Limited Edge Devices","created":"2025-07-13","cited_by_count":0,"area":null},{"id":"2608.08111","title":"Hierarchical Multi-Task Federated Learning in VANETs","created":"2026-08-08","cited_by_count":0,"area":null}],"next_cursor":null}