Nonconvex Regularized Gradient Projection Sparse Reconstruction for Massive MIMO Channel Estimation
IEEE Transactions on Communications（2021）
摘要
Novel sparse reconstruction algorithms are proposed for beamspace channel estimation in massive multiple-input multiple-output systems. The proposed algorithms minimize a least-squares objective having a nonconvex regularizer. This regularizer removes the penalties on a few large-magnitude elements from the conventional $\ell _{1}$ 更多
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关键词
Channel estimation,Approximation algorithms,Massive MIMO,Programming,Optimization,Downlink,Convergence
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