| Abstract: | With the rapid evolution of mobile networks toward 5G and beyond, efficient mobility management
remains a critical challenge, particularly in heterogeneous network (HetNet) environments
characterized by frequent handovers and diverse user requirements.
This report presents the design, simulation, and comparative evaluation of an enhanced
Context-Aware Handover Optimization (CAHO) algorithm developed for improved mobility
control in 5G networks.
The CAHO algorithm dynamically integrates multiple decision metrics including signal
strength (RSRP), cell load, user velocity, SINR, and application-level QoS requirements to
enable robust, energy-efficient, and ping-pong-free handovers. Using a Python-based discrete
event simulator, the proposed CAHO approach is benchmarked against the Auto-Tuning
Optimization (ATO) algorithm and other baseline methods such as threshold-based and
load-aware schemes.
Simulation results demonstrate that CAHO significantly reduces unnecessary handovers
and energy consumption while maintaining seamless connectivity, particularly under variable
speed conditions. This work highlights the potential of context-aware, adaptive algorithms
in enhancing mobility robustness for next-generation networks. |
