Various numerical simulation results indicate that the proposed sparse channel estimation technique outperforms the previous estimation schemes.
Sep 13, 2019 · ABSTRACT Compressed sensing (CS) based channel estimation methods can effectively acquire channel state information for Massive MIMO ...
Missing: Maximization | Show results with:Maximization
PDF | !Compressed sensing (CS) based channel estimation methods can effectively acquire channel state information for Massive MIMO wireless powered.
Sparsity Adaptive Expectation Maximization Algorithm for Estimating Channels in MIMO Cooperation systems · Aihua Zhang, Shouyi Yang, Jianjun Li, Chunlei Li ...
15. Sparsity Adaptive Expectation Maximization Algorithm for Estimating Channels in MIMO Cooperation systems ... Channels in Millimeter-Wave MU-MIMO Systems.
May 9, 2018 · Simulation results show that the proposed algorithm can quickly and accurately recover massive MIMO channel state information with unknown ...
Missing: Expectation Maximization
The Distributed Sparsity Adaptive Matching Pursuit (DSAMP) [7] leverages the spatially common sparsity of massive MIMO channels to jointly estimate multiple ...
Mar 5, 2022 · The study introduces and compares various multiple-input multiple-output (MIMO) channel matrix sparsification methods. A description of the ...
Jul 24, 2021 · By exploiting the sparsity of mm-wave channels, the channel estimation for IRS- assisted MIMO mm-wave systems was formulated as a classical ...
Apr 8, 2013 · Both least mean square (LMS) and least mean fourth (LMF) are popular adaptive algorithms with application to adaptive channel estimation.