MVU estimate of user velocity via gamma distributed handover count in HetNets
R Tiwari, S Deshmukh - IEEE Communications Letters, 2019 - ieeexplore.ieee.org
IEEE Communications Letters, 2019•ieeexplore.ieee.org
In this letter, we propose a handover-count based minimum-variance-unbiased (MVU)
estimate of user velocity in heterogeneous-networks (HetNets). Since mobility management
is considered as critical challenge in success of HetNets, it is imperative to have accurate
estimation of the user velocity. In this context, we consider handover-counts as a measure of
velocity and approximate its probability-mass-function by Gamma distribution. Next, we
exploit Neyman-Fisher-factorization method to extract the sufficient statistics and then …
estimate of user velocity in heterogeneous-networks (HetNets). Since mobility management
is considered as critical challenge in success of HetNets, it is imperative to have accurate
estimation of the user velocity. In this context, we consider handover-counts as a measure of
velocity and approximate its probability-mass-function by Gamma distribution. Next, we
exploit Neyman-Fisher-factorization method to extract the sufficient statistics and then …
In this letter, we propose a handover-count based minimum-variance-unbiased (MVU) estimate of user velocity in heterogeneous-networks (HetNets). Since mobility management is considered as critical challenge in success of HetNets, it is imperative to have accurate estimation of the user velocity. In this context, we consider handover-counts as a measure of velocity and approximate its probability-mass-function by Gamma distribution. Next, we exploit Neyman-Fisher-factorization method to extract the sufficient statistics and then following Rao-Blackwell-Lehmann-Scheffe theorem, we finally derive the MVU estimator. The performance of proposed estimator is verified via numerical analysis in which we observe close match of variance with its corresponding Cramer-Rao-lower-bound.
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