Unmanned Aerial Vehicles (UAVs) hold significant importance in modern technology, requiring seamless integration of autonomous flight capabilities and robust communication systems to effectively perform various roles. Small drones face challenges such as maintaining stable hovering due to atmospheric effects like wind and turbulence. These environmental factors can disrupt the drone's balance and make it difficult for the drone to maintain a consistent position in the air.Therefore, addressing these issues related to hovering, atmospheric effects, and antenna alignment is essential to enhancing the operational efficiency and effectiveness of UAVs in various applications.To tackle and solve these challenges, our project aims to examine real-time communication quality between UAVs and ground stations, leveraging Software-Defined Radio (SDR) technology. We aim to combine the evaluation of communication quality with UAV flight positions in order to obtain useful information for improving Packet Delivery Ratio (PDR) in dynamic spatial situations. The major contributions of this projects are three-fold i) Addressing drone flight patterns and classifying different aerial conditions, ii) Enhancing the existing MCS (Modulation and Coding Scheme) table so it will be aware of aerial and flight conditions ,iii) The exhaustive experimentation on a real test bed, employing a ”train on day, test on the next day” methodology.