3 citations · 8 across the 9 of their papers we have counts for
4 papers · 1 filter
Channel Estimation for Hybrid Massive MIMO Systems with Adaptive-Resolution ADCs
Yalin Wang, Xihan Chen, Yunlong Cai +2
Achieving high channel estimation accuracy and reducing hardware cost as well as power dissipation constitute substantial challenges in the design of massive multiple-input multipl…
Light-SERNet: A lightweight fully convolutional neural network for speech emotion recognition
Arya Aftab, Alireza Morsali, Shahrokh Ghaemmaghami +1
Detecting emotions directly from a speech signal plays an important role in effective human-computer interactions. Existing speech emotion recognition models require massive comput…
Deep-Unfolding Neural-Network Aided Hybrid Beamforming Based on Symbol-Error Probability Minimization
S. Shi, Y. Cai, Q. Hu +2
In massive multiple-input multiple-output (MIMO) systems, hybrid analog-digital (AD) beamforming can be used to attain a high directional gain without requiring a dedicated radio f…
Deep Learning Framework for Hybrid Analog-Digital Signal Processing in mmWave Massive-MIMO Systems
Alireza Morsali, Afshin Haghighat, Benoit Champagne
Hybrid analog-digital signal processing (HSP) is an enabling technology to harvest the potential of millimeter-wave (mmWave) massive-MIMO communications. In this paper, we present…