  Millimeter-wave massive MIMO with lens antenna array can considerably reduce
the number of required radio-frequency (RF) chains by beam selection. However,
beam selection requires the base station to acquire the accurate information of
beamspace channel. This is a challenging task, as the size of beamspace channel
is large while the number of RF chains is limited. In this paper, we
investigate the beamspace channel estimation problem in mmWave massive MIMO
systems with lens antenna array. Specifically, we first design an adaptive
selecting network for mmWave massive MIMO systems with lens antenna array, and
based on this network, we further formulate the beamspace channel estimation
problem as a sparse signal recovery problem. Then, by fully utilizing the
structural characteristics of mmWave beamspace channel, we propose a support
detection (SD)-based channel estimation scheme with reliable performance and
low pilot overhead. Finally, the performance and complexity analyses are
provided to prove that the proposed SD-based channel estimation scheme can
estimate the support of sparse beamspace channel with comparable or higher
accuracy than conventional schemes. Simulation results verify that the proposed
SD-based channel estimation scheme outperforms conventional schemes and enjoys
satisfying accuracy, even in the low SNR region as the structural
characteristics of beamspace channel can be exploited.
