A Modified K-means User Grouping Design for HAP Massive MIMO Systems

Abstract

In this paper, we propose a new user grouping scheme for the high altitude platform (HAP) massive Multiple-Input Multiple-Output (MIMO) systems based on statistical-eigenmode (SE). It has been proved that SE makes a major contribution to signal power for HAPs. Then, a Fubini-Study distance based modified K-means (FS-MKM) user grouping method is proposed aiming at reducing intra-group interference and improving system performance. The proposed modified K-means algorithm improves the initial points selection of the original K-means algorithm. The Fubini-Study distance is obtained based on the SEs of different users. Simulation results confirm that the proposed user grouping algorithm yields significant performance enhancement.