Abstract:
Massive Multiple Input Multiple Output (MIMO)also known as Multi user MIMO is a developing technology having the potential to meet the ever increasing demand of data throughput and E while remaining within the same bandwidth or power resources. This is done by using multiple antennas at the Base Station (BS) and simultaneously serving several user terminals using single/multiple antennas in the same time/frequency resource. Massive MIMO systems make use of the channel reciprocity for the estimation of channel responses during pilot transmission when the uplink is carried out and then use the acquired CSI for both uplink receive combining and downlink transmit pre-coding of payload data. Pilot transmission is not done during downlink. In order to increase the throughput we need accurate Channel State Information (CSI) at the BS. The performance of Linear processing schemes such as Zero Forcing (ZF) reaches almost the same level as that of Non linear processing schemes (DPC/SIC) when the number of antennas at the BS are increased in comparison to the user terminals. But Perfect CSI is assumed while doing this comparison. In this thesis, the impact of Linear processing on Massive MIMO is studied with Imperfect CSI.
