… However, there are few studies on channel estimation using machine learning so far. Only
[8] proposed a machine learning channel estimation algorithm using Gaussian mixture model (…

… accuracy for the massive MIMO channel estimation. Simulation … In Section 2, we first present
the massive MIMO channel … SBL-based method for massive MIMO channel estimation in the …

… , ξi is the Gaussian mixture weight, µi and νxi are the mean and variance of the i-th complex
Gaussian component, and D is the number of complex Gaussian mixture components. We …

… downlink channel estimation of massive MIMO … MIMO channel. Then, based on the variational
expectation maximization (EM) framework [7], we develop an iterative Bayeisan learning …

… , the channel estimation is less problematic for massive MIMO. The … , standard channel
estimation for small scale MIMO-least … For such cases, many methods of channel estimation using …

… address wideband channel estimation in non-stationary uplink massive MIMO, where
orthogonal frequency division multiplexing (OFDM) is adopted to deal with the long channel delay …

… all the unknown parameters of the underlying Bayesian inference … of channel estimation
accuracy, achievable rate, and computational complexity, as compared to the Gaussian mixture …

… -aided Gaussian mixture LAMP (GM-LAMP) based beamspace channel estimation scheme
… that beamspace channel elements can be modeled by the Gaussian mixture distribution, we …

… -SBL) channel estimation algorithm. It is highly beneficial to mmWave massive MIMO systems,
… priors are modeled by a Gaussian-mixture (GM) distribution. Specifically, [25] proposed an …

… consider a channel estimation method based on beamspace sparsity in massive MIMO. We
… , referring to LAMP, we use machine learning to train the nonlinear shrinkage parameter of …