LOS/NLOS Estimators for mmWave Cellular Systems With Blockages

TL;DR

This paper develops Bayesian estimators for mapping LOS/NLOS conditions in mmWave cellular systems, balancing accuracy and computational efficiency, validated through simulations and real urban data.

Contribution

It introduces a practical approximation for the optimal Bayesian LOS map estimator, reducing computational complexity from exponential to quasi-linear.

Findings

The approximation achieves near-optimal accuracy.

The heuristic estimator performs well with low computational cost.

Validations include synthetic and real urban layouts.

Abstract

Designers of millimeter wave (mmWave) cellular systems need to evaluate line-of-sight (LOS) maps to provide good service to users in urban scenarios. In this letter, we derive estimators to obtain LOS maps in scenarios with potential blocking elements. Applying previous stochastic geometry results, we formulate the optimal Bayesian estimator of the LOS map using a limited number of actual measurements at different locations. The computational cost of the optimal estimator is derived and is proven to be exponential in the number of available data points. An approximation is discussed, which brings the computational complexity from exponential to quasi-linear and allows the implementation of a practical estimator. Finally, we compare numerically the optimal estimator and the approximation with other estimators from the literature and also with an original heuristic estimator with good performance and low computational cost. For the comparison, both synthetic layouts and a real layout of Chicago have been used.