An Effective Path Planning Optimization in Cellular Networking Based on Key Performance Indicator: A Review

The advancement of cellular network (CN) technologies is driven by the exponential growth of mobile users and their increasing demand for data consumption. To meet these demands, efficient Path Planning (PP) within CNs is crucial for achieving better throughput, latency, and overall network efficiency. This paper explores various PP approaches, including genetic algorithms, optimization algorithms, neural networks, and planning algorithms, utilized to find collision-free paths with minimal energy and time consumption for data transmission. Evaluation of these approaches involves analyzing Key Performance Indicators (KPIs) to identify areas for improvement in network deployments. Throughput, bandwidth, latency, peak data rates, peak spectral efficiency, network resources, average transmission rate, energy efficiency, energy consumptions, accuracy, Reference Signal Received Quality (RSRQ), SINR, Reference Signal Received Power (RSRP), are used as KPI parameters. The effectiveness of PP methods is essential not only for enhancing network capacity but also for enabling applications such as wireless communication devices, Unmanned Aerial Vehicles (UAVs), and Mobile Robots (MRs) to perform preventive and corrective actions in emergency situations. This review provides insights into the significance of PP in optimizing CN performance and surveys the latest approaches aimed at reducing latency and enhancing network capacity for efficient data transmission.