This research study aims to develop a Feed Forward Deep Neural Network model for PL Prediction for Fifth Generation Wireless Communication Networks. The objectives of the study include:

1. To develop a Feed Forward Deep Neural Network (FFDNN) model that optimizes Random Search utilizing back Propagation.
2. To implement fault-tolerant mechanisms within deep learning models to enhance reliability and robustness for PL prediction in 5G networks
3. To Predict PL Using Broader Frequency Range for Wireless Communication Channel Relevant to 5G Networks.
4. To Identify Key Indicators of Prediction Model for PL Using Deep Neural Network.