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Task-Oriented Multi-User Semantic Communications
Huiqiang Xie, Zhijin Qin, Xiaoming Tao +1
While semantic communications have shown the potential in the case of single-modal single-users, its applications to the multi-user scenario remain limited. In this paper, we inves…
Learn to Communicate with Neural Calibration: Scalability and Generalization
Yifan Ma, Yifei Shen, Xianghao Yu +3
The conventional design of wireless communication systems typically relies on established mathematical models that capture the characteristics of different communication modules. U…
Neural Calibration for Scalable Beamforming in FDD Massive MIMO with Implicit Channel Estimation
Yifan Ma, Yifei Shen, Xianghao Yu +3
Channel estimation and beamforming play critical roles in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. However, these two modules have…
Over-the-Air Computation via Reconfigurable Intelligent Surface
Wenzhi Fang, Yuning Jiang, Yuanming Shi +3
Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition prope…
Delay Analysis of Wireless Federated Learning Based on Saddle Point Approximation and Large Deviation Theory
Lintao Li, Longwei Yang, Xin Guo +4
Federated learning (FL) is a collaborative machine learning paradigm, which enables deep learning model training over a large volume of decentralized data residing in mobile device…