A novel method for estimating propagation pathloss in millimeter-wave communication systems

Abstract

In millimeter wave communication systems, the construction of a path loss model that is close to empirical one plays an important role in planning coverage, system capacity, and link budgets. In this paper, we propose a novel approach applied unsupervised machine learning for propagation pathloss estimation in millimeter wave communication systems based on the iterative procedure of cooperative and iterative evaluation exchange (Co-IEE) algorithm. The propagation path loss models of the time city–an urban area in the center of Hanoi, Vietnam in both line-of-sight (LOS) and non line-of-sight (NLOS) are estimated and calculated using the proposed approach and then they are compared to the minimum mean square error (MMSE). The estimated results of the proposed model show the approximation with the optimum one returned by MMSE method. Moreover, the proposed model of estimating path loss can solve the problem of sensitivity with outliers existing in MMSE and give more choices for path loss exponents.