  The updated physical layer standard of the fifth generation wireless
communication suggests the necessity of a rapid prototyping platform. To this
end, we develop RaPro, a multi-core general purpose processor-based massive
multiple-input-multiple-output (MIMO) prototyping platform. To enhance RaPro,
high performance detection and beamforming are needed, whereas both of them
request for accurate channel state information (CSI). In this paper, linear
minimum mean square error (LMMSE)-based channel estimator is adopted and
encapsulated inside RaPro to gain more accurate CSI. Considering the high
comlexity and unknown of channel statistics, we design low-complexity LMMSE
channel estimator to alleviate the rising complexity along with increasing
antenna number and set more computational resource aside for massive MIMO
uplink detection and downlink beamforming. Simulation results indicate the high
mean square error performance and robustness of designed low-complexity method.
Indoor and corridor scenario tests show prominent improvement in bit error rate
performance. Time cost analysis proves the practical use and real-time
transmission ability of the implemented uplink receiver on RaPro.
