  Hybrid beamforming is a promising technology for 5G millimetre-wave
communications. However, its implementation is challenging in practical
multiple-input multiple-output (MIMO) systems because non-convex optimization
problems have to be solved, introducing additional latency and energy
consumption. In addition, the channel-state information (CSI) must be either
estimated from pilot signals or fed back through dedicated channels,
introducing a large signaling overhead. In this paper, a hybrid precoder is
designed based only on received signal strength indicator (RSSI) feedback from
each user. A deep learning method is proposed to perform the associated
optimization with reasonable complexity. Results demonstrate that the obtained
sum-rates are very close to the ones obtained with full-CSI optimal but complex
solutions. Finally, the proposed solution allows to greatly increase the
spectral efficiency of the system when compared to existing techniques, as
minimal CSI feedback is required.
