Channel Estimation and Precoding for Massive Mimo Downlink Time –Division Duplex System

Abstract

The massive MIMO technology uses a large number of antennas at the base station to transmit and receive signals using a Time Division Duplex (TDD) to/from users at the same time and the same frequency but with different time slot for uplink and downlink transmission. This gives a high spectral efficiency and improves reliability. In a massive MIMO downlink system the channel is estimated using uplink training by sending an orthogonal pilot sequence from users to the base station. The orthogonal pilot sequence is known at the base station and can be used to estimate the channel. This estimated channel is used to precode data at the base station for downlink transmission. Due to the coherence time limitation, the orthogonal sequence are re-used in different cells, causing the base station to receive non-orthogonal pilot sequence from adjacent cells which have an impact in estimating the channel. This channel estimation error is known as pilot contamination. In this thesis, a pre-coder technique for massive MIMO downlink TDD system is developed by considering the impact of pilot contamination in the estimating of a channel. Considering the impact of pilot contamination, a pilot reuse factor is designed to develop a novel uplink training scheme which enables an optimal estimate of the channel. The optimal estimated channel is used to develop a large scale fading precoder. A large scale fading precoding system is applied together with pilot reuse factor to mitigate the pilot contamination effect. This achieves a higher transmission rate over existing method. From simulation results obtained using MATLAB, an improvement on the 5% outage rate 10 times over the existing method has been realized. This is a significant improvement but obtained at the expense of sub-array BS installation and power consumption.