UC Irvine

The number of connected wireless devices is anticipated to increase heavily in the next few years. Thus, there is a need for a new system which is able to handle billions of wireless devices. The category of massive multiple input multiple output (MIMO) systems is a great candidate for this purpose. Because of the large number of antennas in massive MIMO there is a need to reduce the dimension of the MIMO channel effectively to decrease the complexity. This could be achieved by using a particular prebeamforming technique that is introduced recently. An important aspect of wireless communication systems is the channel state information (CSI). In order to send and receive data through the channel, the transmitter and the receiver must know the CSI or at least have an estimation for it. In this thesis, different algorithms for estimating the channel vector coefficient and their performance are studied. Different approaches are used in order to find the best algorithm based on the performance of the estimating channel and the complexity of the algorithm. Also, algorithms are used to estimate the channel vector coefficient for different channel models.