Data-Assisted Channel Estimation for Uplink Massive MIMO Systems

A novel data- assisted channel estimation scheme is proposed for uplink massive multiple- input multiple- output ( MIMO) systems to alleviate the performance bottleneck due to pilot contamination. Specifically, the uplink resource within a fading block is first divided into a number of data blocks, which are encoded respectively; then the detected data blocks are utilized iteratively to refine the channel estimation, improving the signal- to- interference- plus- noise ratio ( SINR) of the following data blocks. In the existing literature, the system performance can not scale up with the number of base station's antenna due to the effect of pilot contamination. The proposed scheme provides a promising approach to improve the uplink SINR by the order Theta(LM/L + M) without increasing the length of pilot sequence, where L and M are the number of transmission symbols within a fading block and the number of base station's antennas respectively. It is shown by simulations that the uplink performance of massive MIMO systems is significantly increased by the proposed scheme.