Artificial Intelligence Techniques for Cooperative Unmanned Aerial Vehicles Assisted Wireless Networks

In this research work, we will study the performance of cellular networks using cooperative unmanned aerial vehicles (UAV) assisted wireless networks. The UAVs will assist the existing wireless network structure to enhance the network coverage, quality of service, and disaster recovery. Multiple UAVs are assumed to work individually or to collaborate to transmit the data from the base station to the intended users or sensor and vise-versa. These vehicular nodes are supposed to be intelligent to change their positions in the three dimensional space, adjust their velocity and control their transmitting power in order to enhance the performance of the wireless network. Therefore, artificial intelligence techniques will be used to improve the quality of service experienced by the users. Different artificial intelligence techniques with relying protocols will be proposed to make the UAVs smart enough to enhance the system performance. Some energy efficient routing algorithms for internet of things (IoT) sensors using fuzzy logic could be also proposed in this research work. We will derive analytical expressions for the system coverage probability, area spectral efficiency and energy efficiency assuming the communications channels are suffering from fading and noise. We will also consider the line-of-site and non-line-of-site models used in air-to-ground communications. The system performance will be studied at high signal-to-noise ratio (SNR) regime where the coverage probability will be approximated and analyzed in terms of coding gain and diversity order. Monte-Carlo simulations and some practical numerical examples will be provided to validate the obtained expressions and to illustrate the effect of various system parameters on the performance of the system. To enhance the system performance different AI techniques will be used to maximize the system coverage probability in terms of UAVs placement and transmission power. The derived results are expected to provide a deep insight to the impact of employing the UAVs technologies with AI assistance on the performance of wireless networks. This research project will contribute significantly to the Kingdom of Saudi Arabia's innovation agenda as well as to the local research community at KFUPM University.