Max-Min fairness-based resource allocation in massive MIMO systems

This work deals with power and spectrum allocation approaches for massive MIMO (M-MIMO) systems. An analysis is made to verify the efficiency of the solutions provided by schemes used for the spectral and energy efficiency (SE-EE) trade-off problem in massive antenna-based wireless communication systems. We first introduce the  Geometry Based Stochastic Model (GBSM) channel model (One-ring model), describing the behavior of a uniform linear array of antennas (ULA) arrangement, revealing how the channel parameters affect the channel capacity. We also show that under this model, the SE still increases without boundary when the massive number of base-station (BS) antennas $M$ increases, provided that pilot contamination is substantially mitigated or eliminated but when the number of users equipment (UEs) $K$ increases with a fixed number of antennas in the BS, there is a increasing limitation from the combiners in mitigating the inter-user interference, making decoding difficult. The downlink (DL) M-MIMO scenario is analyzed, by introducing the generalized power allocation problem and derived the max-min fairness scheme from it. We propose a procedure to solve the max-min problem and