Abstract: An electronic device and a method for path optimization for unmanned aerial system (UAS) is provided. The electronic device includes a memory to store a machine learning model to be trained. The electronic device retrieves a first plurality of parameters related to one or more wireless environments to be utilized by the UAS and generates signal-to-interference-plus-noise ratio (SINR) heatmap information. The electronic device further generates state space information based on the generated SINR heatmap information and trains the machine learning model based on the generated state space information. The trained machine learning model indicates one or more movement based actions to be taken by the UAS at a plurality of states defined in the generated state space information. The electronic device further controls the UAS to travel a predefined path in at least one of the one or more wireless environments based on the trained machine learning model.