Energy-Efficiency Maximization of Hybrid Massive MIMO Precoding With Random-Resolution DACs via RF Selection

Energy-efficiency (EE) is identified as a key 5G metric and will have major impact on the hybrid beamforming system design. The most promising designs include reduced number of radio-frequency (RF) chains with digital-to-analog converters (DACs) lower sampling resolution. However, naive reduction beamformer components to reduce power consumption typically leads significant loss spectral-efficiency (SE). In this paper, we focus transmit (precoding) introduce an architecture low-end that maximizes EE while minimizing effects SE. This achieved by novel design analog part precoder, where RF not priori, but deactivated based optimization algorithm. Thus, problem becomes subset selection one, only optimal SE-EE performance are being activated. algorithm determines activate also selects optimally between DACs randomly-allocated Through simulations, verify proposed exhibits improved when compared baseline precoding techniques which use predefined low-resolution DACs.