11 citations · 11 across the 5 of their papers we have counts for
5 papers
Learned Trimmed-Ridge Regression for Channel Estimation in Millimeter-Wave Massive MIMO
Pengxia Wu, Julian Cheng, Yonina C. Eldar +1
Channel estimation poses significant challenges in millimeter-wave massive multiple-input multiple-output systems, especially when the base station has fewer radio-frequency chains…
Sparse Channel Reconstruction With Nonconvex Regularizer via DC Programming for Massive MIMO Systems
Pengxia Wu, Hui Ma, Julian Cheng
Sparse channel estimation for massive multiple-input multiple-output systems has drawn much attention in recent years. The required pilots are substantially reduced when the sparse…
Nonconvex Regularized Gradient Projection Sparse Reconstruction for Massive MIMO Channel Estimation
Pengxia Wu, Julian Cheng
Novel sparse reconstruction algorithms are proposed for beamspace channel estimation in massive multiple-input multiple-output systems. The proposed algorithms minimize a least-squ…
Deep Unfolding Basis Pursuit: Improving Sparse Channel Reconstruction via Data-Driven Measurement Matrices
Pengxia Wu, Julian Cheng
For massive multiple-input multiple-output (MIMO) systems operating in frequency-division duplex mode, downlink channel state information (CSI) acquisition will incur large overhea…
Compressed CSI Feedback With Learned Measurement Matrix for mmWave Massive MIMO
Pengxia Wu, Zichuan Liu, Julian Cheng
A major challenge to implement the compressed sensing method for channel state information (CSI) acquisition lies in the design of a well-performed measurement matrix to reduce the…