Implementation trade-offs for linear detection in large-scale MIMO systems

In this paper, we analyze the VLSI implementation tradeoffs for linear data detection in the uplink of large-scale multiple-input multiple-output (MIMO) wireless systems. Specifically, we analyze the error incurred by using the sub-optimal, low-complexity matrix inverse proposed in Wu et al., 2013, ISCAS, and compare its performance and complexity to an exact matrix inversion algorithm. We propose a Cholesky-based reference architecture for exact matrix inversion and show corresponding implementation results on an Virtex-7 FPGA. Using this reference design, we perform a performance/complexity trade-off comparison with an FPGA implementation for the proposed approximate matrix inversion, which reveals that the inversion circuit of choice is determined by the antenna configuration (base-station antennas vs. number of users) of large-scale MIMO systems.