Hybrid Pseudo-Bayesian Estimation in Random Access-Based Tactical FANETs

Abstract

In random access-based tactical flying ad-hoc networks, frequent packet collisions degrade network performance severely. To prevent packet collisions, it is imperative to accurately estimate the number of active UAVs (unmanned aerial vehicles); thus, this paper proposes an estimation method for the number of active UAVs based on pseudo-Bayesian estimation by combining the pure-Bayesian method and the pseudo-Bayesian method. Through intensive simulations, it is confirmed that the proposed method outperforms the various existing methods.