Impairment Mitigation in Narrowband Land Mobile Radio System using Integrated Deep Learning Framework

Land Mobile Radio is a narrowband two-way wireless communication system developed for public safety operations and emergency response. The wireless communication channel can disrupt the transmission of signals with various impairments, from interference to noise. To mitigate these impairments, interference cancellation and channel estimation methods are required to ensure reliable communication. Thus, data-driven Deep Learning-based approaches for impairment mitigation are investigated and developed for Land Mobile Radio signals. The outcomes of this research have the potential to provide learning-based solutions to overcome the major impairments that affect the performance of the receiver in wireless communication systems.