Implementation of Massive MIMO Uplink Receiver on RaPro Prototyping Platform

TL;DR

This paper presents RaPro, a multi-core platform for massive MIMO uplink, featuring a low-complexity LMMSE channel estimator that improves accuracy and robustness, enabling real-time high-performance wireless communication.

Contribution

Development of RaPro platform with a novel low-complexity LMMSE channel estimator for massive MIMO uplink detection and beamforming.

Findings

High mean square error performance and robustness of the estimator.

Significant bit error rate improvements in indoor and corridor tests.

Real-time transmission capability demonstrated through time cost analysis.

Abstract

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.