$P$ -Persistent Energy-Aware Handover Decisions Employing RF Fingerprint for Adaptive-Sized Heterogeneous Cellular Networks

Abstract

The diverse architectural evolution and intensive data explosion in the forthcoming 5G will have severe impacts on providing seamless and robust mobility management. In this paper, P-persistent energyaware handover (HO) decision strategies with mobility robustness are proposed both for intra-handover cases while a femto user equipment (FUE) roams into another femto access point (FAP) and for cross-tier handover cases while a macro user equipment (MUE)/FUE roams into/out of the FAP in a dynamic cell sizing involving macro-femto two-tier networks. To approximate the densely deployed small-cells, a unique RF fingerprint (RFF)-based localization is employed to enable efficient small-cell detection by an RFF matching mechanism. The prediction of the HO trigger is jointly determined by a P-persistent decision mechanism that formulates the specific HO behaviors when an MUE/FUE roams into (HO-in) and out of (HO-out) a femtocell in terms of the correlated coverage variance and UE trajectory features, whereas the target selection follows a utility function in consideration of the UE traveling time and the achievable throughput. The closed-form stationary probabilities of the proposed VHO/HHO decisions are analyzed by a Semi-Markov-based framework. In addition, an adjustable sensing mechanism with dynamic intervals is proposed when UE is located far from the RFF matching region, which can have a positive influence on reducing unnecessary UE energy consumption. Numerical results are presented for the decision accuracy analyses (too early, too late, and ping-pong HOs), energy-efficiency, and resource utilization of the two-tier system. The comprehensive evaluations indicate that the proposed scheme can enhance the mobility robustness and enable an optimal trade-off between the energy efficiency (EE) and system capacity while eliminating the architectural impacts caused by the dynamic topology and the dense deployment for the next-generation macro-femto two-tier networks. INDEX TERMS Horizontal and vertical handover, cell discovery, RF fingerprint, dynamic localization, energy-aware, RAT selection.

A survey on the handover management in 5G-NR cellular networks: aspects, approaches and challenges

“…The FAP is selected according to UE's traveling time and achievable capacity and the probability of transition between vertical and horizontal handovers is derived via a semi-Markov model. To be more precise in selecting the FAP, the probability to handover is regularly measured in RFF region, but it is limited to a dynamic sensing interval to save energy by canceling the excessive measurements and skipping non-proper handovers [106]. However, most of the mathematical models apply the single-input memoryless exponential distribution which is not capable of depicting a multi-dimensional entity for handover requests.…”

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