  A hybrid architecture for millimeter wave (mmW) massive MIMO systems is
considered practically implementable due to low power consumption and high
energy efficiency. However, due to the limited number of RF chains, user
selection becomes necessary for such architecture. Traditional user selection
algorithms suffer from high computational complexity and, therefore, may not be
scalable in 5G and beyond wireless mobile communications. To address this
issue, in this letter we propose a low complexity CNN framework for user
selection. The proposed CNN accepts as input the channel matrix and gives as
output the selected users. Simulation results show that the proposed CNN
performs close to optimal exhaustive search in terms of achievable rate, with
negligible computational complexity. In addition, CNN based user selection
outperforms the evolutionary algorithm and the greedy algorithm in terms of
both achievable rate and computational complexity. Finally, simulation results
also show that the proposed CNN based user selection scheme is robust to
channel imperfections.
