Enhancing Smart City Connectivity: Implementing Channel-Adaptive Strategies for FSO-Based Drone-Assisted Mobile Access Networks in Urban Environments

The global surge in urbanization has catalyzed the evolution of smart city infrastructures, characterized by expansive interconnected networks spanning vast urban landscapes. To address the connectivity challenges inherent in smart city environments, this study advocates for the utilization of autonomous aerial vehicles (AAVs) as an alternative to traditional mobile air base stations. Leveraging Free-Space Optical (FSO) links for downlink transmission from AAVs to users, the proposed system confronts atmospheric turbulence and pointing loss impairments. In this context, the study explores the average spectral efficiency (ASE) performance of the proposed FSO-based Drone-Assisted system employing various channel adaptive techniques, including Optimal Rate Adaptation, Channel Inversion with Fixed Rate, Optimal Power and Rate Adaptation, and Truncated Channel Inversion with Fixed Rate. Additionally, the investigation underscores the impact of factors such as link range, coverage distance, AAV orientation fluctuation standard deviation, AAV position vibration standard deviation, and beam divergence on system performance. By elucidating these aspects, the research aims to contribute valuable insights into the optimization of smart city connectivity, paving the way for enhanced communication infrastructure in urban environments. Notably, the study achieved a maximum ASE of 101 bits/s/Hz using the TIFR adaptation scheme, underscoring the efficacy of the proposed approach.