Analysis of Drone Wireless Communication System Performance Affected by Vibration based on 1DCNN

Developments in drone technology have made them crucial in various fields. Vibrations caused by external conditions or mechanical failures in a drone's design can significantly affect the efficiency of the drone's communication systems. The drone's antenna generates phase noise, which can degrade the performance of drone communications systems. This work presents an analysis and computational model of how drone vibration affects system performance. by using two steps. The first one uses the simulation Monte-Carlo in MATLAB when the iteration algorithm processes with various variable values as the frequency carriers and the order of the quadrature-amplitude-modulation (M-QAM) system and evaluates the performance of the communication system by measuring the symbol error rate. The second step uses the one-dimensional convolutional neural network to predict the symbol error rate. After creating the dataset in the first stage, reprocess it and split it into 70% training and 30% testing. Then, by MATLAB App Designer created a graphical user interface (GUI) for friendly use. The result appears to be that the performance of the drone communication system decreased when frequency carriers and modulation order for M-QAM increased due to the impact of a vibrating antenna. Our contribution to this work is using 1DCNN, unlike other works that only use simulation to evaluate the performance, because 1DCNN can automatically extract useful features from the input dataset to evaluate the effect. This study provides a valuable method to evaluate the efficiency of a communication system on the UAV, which is particularly important for drone wireless system planning. In our next work, we propose investigating other factors affecting UAV communication systems, including humidity and temperature.