An Improved Dropping Algorithm for Line-of-Sight Massive MIMO With Tomlinson-Harashima Precoding

One of the problems in line-of-sight massive MIMO is that a few users can have correlated channel vectors. To alleviate this problem, a dropping algorithm has been proposed in the literature, which drops some of the correlated users to make the spatial correlation among the remaining users be less than a certain threshold. Thresholds were found by running a large number of simulations. In this letter, the same dropping algorithm is analyzed for a known nonlinear precoder: Tomlinson-Harashima precoder. Instead of simulation-based thresholds, closed-form analytical expressions are derived in this letter for two power allocation schemes: max-min and equal received power control schemes. It is shown that the derived thresholds are optimal in terms of achievable sum-rate when there is only one correlated pair of users. For channels with multiple pairs of correlated users, simulation results show that using the derived thresholds improves the 5th percentile sum-rate. Due to the fairness criterion of max-min, the improvement for max-min power control is much higher than equal received power control.