Multi-Objective Optimization for Dynamic Resource Allocation in Heterogeneous Uncrewed Aerial Vehicles-Base Station

Abstract

In response to the increasing energy demands of mobile networks, particularly due to the imbalanced usage between urban and suburban areas, this study presents a heterogeneous UAV-based station architecture within a C-RAN framework as a novel solution. This architecture aims to reshape next-generation networks by offering high reconfigurability and mobility. Central to this system is the dynamic adaptability of the BBU pool, which connects to the RRH, allowing real-time adjustments based on shifting usage demands. This flexibility plays a vital role in reducing energy consumption, especially in dynamic and fluctuating network environments. To optimize the architecture's performance, the study addresses the trade-offs between handover frequency, transmission delay, and power consumption by formulating a multi-objective optimization problem. Two resource allocation strategies based on meta-heuristic algorithms are proposed: GARAH and SARAH. GARAH prioritizes minimizing energy consumption and delay time, demonstrating its effectiveness through simulations. SARAH, on the other hand, achieves a balance by maintaining energy efficiency and low latency while reducing handover occurrences. These strategies highlight the potential of the heterogeneous UAV-based C-RAN architecture to foster more sustainable, efficient, and adaptable mobile networks.