QoS-Aware Route Navigation for Pedestrians Using 5G Cellular Networks

Qiyu Jiang, Xing Tang, Jing Wang

Abstract: Route planning is a fundamental service for pedestrians navigating unfamiliar environments. Existing solutions often need to pay more attention to considering Quality of Service (QoS) requirements in the context of 5G cellular networks, a crucial aspect for enhancing user experiences. In this paper, we delve into the problem of QoS-aware dynamic path planning for pedestrians in 5G cellular networks, which presents itself as a multi-constrained optimization problem. To tackle this challenge, we merge the dynamic A* algorithm with Ant Colony Optimization (ACO) to determine the shortest path dynamically while ensuring QoS prerequisites. First, we employ a Markov prediction model and population statistics to forecast statechanging information. Second, we employ a retroactive priority queue to enhance the dynamism of the A* search algorithm. Then, we introduce a reference value generated by ACO to streamline the search space of A*. Finally, simulation results demonstrate our proposed method’s effectiveness and efficiency.