A fast channel estimation and the reduction of pilot contamination problem for massive MIMO based on a diagonal Jacket matrix

Wireless channels are usually multipath fading channel. The large and small scale fading is used in massive multiple-input and multiple-output (MIMO) channel. The large scale fading channel matrix accounts shadow fading and path loss and the small scale fading channel accounts a changeable wavelength. In this paper we assume perfect multipath fast channel estimation and the reduction of a a pilot contamination problem for massive MIMO based on a diagonal Jacket matrix. Many advantages of diagonal Jacket matrices such as excellent eigenvector for the matter of pilot contamination, sample eigenvalue based detection of signals, reduce the computational complexity, possible use of fast Fourier transforms (FFT) for the fast channel estimation, a constant diagonal treatment and an energy harvest. The diagonal Jacket matrices are constructed by a Jacket and a circulant Jacket matrix that provides the excellent eigenvalue decomposition based way to massive MIMO channel estimation which improves the performance and the channel accuracy. In this paper we also compare the diagonal Jacket based iterative least-square with projection (ILSP) method and a minimum mean square error (MMSE) based linear channel estimation strategies.