93 citations · 104 across the 6 of their papers we have counts for
10 papers
Role of Deep Learning in Wireless Communications
Wei Yu, Foad Sohrabi, Tao Jiang
Traditional communication system design has always been based on the paradigm of first establishing a mathematical model of the communication channel, then designing and optimizing…
Learning Progressive Distributed Compression Strategies from Local Channel State Information
Foad Sohrabi, Tao Jiang, Wei Yu
This paper proposes a deep learning framework to design distributed compression strategies in which distributed agents need to compress high-dimensional observations of a source, t…
Hybrid Analog and Digital Beamforming Design for Channel Estimation in Correlated Massive MIMO Systems
Javad Mirzaei, Shahram ShahbazPanahi, Foad Sohrabi +1
In this paper, we study the channel estimation problem in correlated massive multiple-input-multiple-output (MIMO) systems with a reduced number of radio-frequency (RF) chains. Imp…
Deep Active Learning Approach to Adaptive Beamforming for mmWave Initial Alignment
Foad Sohrabi, Zhilin Chen, Wei Yu
This paper proposes a deep learning approach to the adaptive and sequential beamforming design problem for the initial access phase in a mmWave environment with a single-path chann…
Deep Learning for Distributed Channel Feedback and Multiuser Precoding in FDD Massive MIMO
Foad Sohrabi, Kareem M. Attiah, Wei Yu
This paper shows that deep neural network (DNN) can be used for efficient and distributed channel estimation, quantization, feedback, and downlink multiuser precoding for a frequen…
Multi-Cell Sparse Activity Detection for Massive Random Access: Massive MIMO versus Cooperative MIMO
Zhilin Chen, Foad Sohrabi, Wei Yu
This paper considers sparse device activity detection for cellular machine-type communications with non-orthogonal signatures using the approximate message passing algorithm. This…