3 citations · 6 across the 5 of their papers we have counts for
6 papers
Deep Learning for Joint Design of Pilot, Channel Feedback, and Hybrid Beamforming in FDD Massive MIMO-OFDM Systems
Junyi Yang, Weifeng Zhu, Shu Sun +3
This letter considers the transceiver design in frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) syst…
Deep-Reinforcement-Learning-Based Scheduling with Contiguous Resource Allocation for Next-Generation Cellular Systems
Shu Sun, Xiaofeng Li
Scheduling plays a pivotal role in multi-user wireless communications, since the quality of service of various users largely depends upon the allocated radio resources. In this pap…
Channel Type Recognition in Wireless Communications: A Deep Learning Approach
Shu Sun, Xiaofeng Li, Sungho Moon
In this paper, we propose two novel and practical deep-learning-based algorithms to solve the wireless channel type (WCT) recognition problem. Specifically, the WCT recognition pro…
Deep Learning for Direct Hybrid Precoding in Millimeter Wave Massive MIMO Systems
Xiaofeng Li, Ahmed Alkhateeb
This paper proposes a novel neural network architecture, that we call an auto-precoder, and a deep-learning based approach that jointly senses the millimeter wave (mmWave) channel…
Generative Adversarial Estimation of Channel Covariance in Vehicular Millimeter Wave Systems
Xiaofeng Li, Ahmed Alkhateeb, Cihan Tepedelenlioğlu
Enabling highly-mobile millimeter wave (mmWave) systems is challenging because of the huge training overhead associated with acquiring the channel knowledge or designing the narrow…
Optimal Training for Residual Self-Interference for Full Duplex One-way Relays
Xiaofeng Li, Cihan Tepedelenlioğlu, Habib Şenol
Channel estimation and optimal training sequence design for full-duplex one-way relays are investigated. We propose a training scheme to estimate the residual self-interference (RS…