  One way to reduce the power consumption in large-scale multiple-input
multiple-output (MIMO) systems is to employ low-resolution analog-to-digital
converters (ADCs). In this paper, we investigate antenna selection for
large-scale MIMO receivers with low-resolution ADCs, thereby providing more
flexibility in resolution and number of ADCs. To incorporate quantization
effects, we generalize an existing objective function for a greedy
capacity-maximization antenna selection approach. The derived objective
function offers an opportunity to select an antenna with the best tradeoff
between the additional channel gain and increase in quantization error. Using
the generalized objective function, we propose an antenna selection algorithm
based on a conventional antenna selection algorithm without an increase in
overall complexity. Simulation results show that the proposed algorithm
outperforms the conventional algorithm in achievable capacity for the same
number of antennas.
