multiple-input multiple-output

To overcome the problem of channel estimation in massive multiple-input multiple-output (M-MIMO) systems, in this paper we propose a downlink link channel estimation scheme in frequency-division duplex (FDD) based on structured compressive sensing to reduce the pilot required by which Intrinsic spatial sparsity of M-MIMO delay channels are amplified. For this purpose, first, after discussing the different methods of channel estimation and examining the existing challenges, we define our roadmap and propose our algorithm, in which we estimate the channel based on the greedy orthogonal matching pursuit (OMP) algorithm. In this algorithm, spatial correlation between the channel impulse response of different transmitter antennas is used for accurate channel estimation. This algorithm obtains the channel sparsity in an adaptive way, which negates the ideal assumption of the previous works that the channel sparsity is in hand. In this case, this algorithm estimates the channel with good accuracy in cases when the exact amount of channel sparsity is not known. Finally, we present simulations that demonstrate the ability of this method to reduce the required pilot. The simulations show that the proposed channel estimation reliably obtains the channel sparsity level and the support set compared to similar methods.

In recent years, the use of MIMO systems has been increased dramatically in telecommunication systems, because of their important advantages. In the 4GPP systems, the quality of service should be very high to provide video communications everywhere and every time. The MIMO technology can answer to this requirement. The performance of mobile communication systems is much related to the radio channel. Hence, the prediction of propagation characteristics between both antennas is important in wireless networks. In this paper, the radio channel is predicted between the transmitter and receiver by the use of Uniform Theory of Diffraction (UTD) and extract MIMO channel matrix. The UTD method helps that without the need for expensive measurements, the performance of MIMO systems are investigated. Moreover, the channel capacity is calculated using the channel matrix. To validate our proposed model, the simulation results are compared with the experimental data. There are good agreements between the measurements and the result obtained from the proposed model which justifies the theoretical work.