Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations

摘要

Large-scale (or massive) multiple-input multiple-output (MIMO) is expected tobe one of the key technologies in next-generation multi-user cellular systems,based on the upcoming 3GPP LTE Release 12 standard, for example. In this work,we propose - to the best of our knowledge - the first VLSI design enablinghigh-throughput data detection in single-carrier frequency-division multipleaccess (SC-FDMA)-based large-scale MIMO systems. We propose a new approximatematrix inversion algorithm relying on a Neumann series expansion, whichsubstantially reduces the complexity of linear data detection. We analyze theassociated error, and we compare its performance and complexity to those of anexact linear detector. We present corresponding VLSI architectures, whichperform exact and approximate soft-output detection for large-scale MIMOsystems with various antenna/user configurations. Reference implementationresults for a Xilinx Virtex-7 XC7VX980T FPGA show that our designs are able toachieve more than 600 Mb/s for a 128 antenna, 8 user 3GPP LTE-based large-scaleMIMO system. We finally provide a performance/complexity trade-off comparisonusing the presented FPGA designs, which reveals that the detector circuit ofchoice is determined by the ratio between BS antennas and users, as well as thedesired error-rate performance.