Efficient Power Control Strategies for Massive MIMO in High-Density Massive IoT Networks

We investigate the effectiveness of simple and efficient downlink power control schemes for Massive multiple-input multiple-output (MIMO) systems in high-density massive IoT networks. The complexity and delay of sophisticated power control schemes make them unsuitable for high-density massive IoT situation, necessitating the development of simpler alternatives. We examine two such schemes, equal power allocation and max-min fairness power control, analyzing their performance through signal-to-interference-plus-noise ratio (SINR) derivation in scenarios with and without uplink reference signal (RS) power control. We find that equal power allocation provides high spectral efficiency (SE) but not high fairness, while max-min fairness power control provide high fairness, but requires more complexity and channel state information (CSI) knowledge. However, the performance of max-min fairness power control becomes similar to that of equal power allocation in some cases, suggesting the suitability of the simpler scheme for system performance enhancement. We also propose an algorithm to reduce power consumption through initial radiation power determination. Our findings provide valuable insights into the effectiveness of power control schemes for Massive MIMO in high-density massive IoT networks.