Journal
2021 IEEE 12TH LATIN AMERICA SYMPOSIUM ON CIRCUITS AND SYSTEM (LASCAS)
Volume -, Issue -, Pages -Publisher
IEEE
DOI: 10.1109/LASCAS51355.2021.9459171
Keywords
Massive MIMO; approximate matrix inversion; stair matrix; Gauss Seidel; Neumann Series; MIMO detection; FPGA; VLSI
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This paper presents a VLSI architecture and FPGA implementation of an iterative detection algorithm based on a stair matrix, which supports massive MIMO systems with high data rate and clock frequency, providing superior error-rate performance compared to most contemporary detectors.
Approximate matrix inversion based methods is widely used for linear massive multiple-input multiple-output (MIMO) received symbol vector detection. Such detectors typically utilize the diagonally dominant channel matrix of a massive MIMO system. Instead of diagonal matrix, a stair matrix can be utilized to improve the error-rate performance of a massive MIMO detector. In this paper, we present very large-scale integration (VLSI) architecture and field programmable gate array (FPGA) implementation of a stair matrix based iterative detection algorithm. The architecture supports a base station with 128 antennas, 8 users with single antenna, and 256 quadrature amplitude modulation (QAM). The stair matrix based detector can deliver a 142.34 Mbps data rate and reach a clock frequency of 258 MHz in a Xilinx Virtex-7 FPGA. The detector provides superior error-rate performance and higher scaled throughput than most contemporary massive MIMO detectors.
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