GenAI-Enabled Network Design: ABEP of SC Diversity Under the Combined Effects of Rician Fading and Rician Co-Channel Interference in WCN Case Study

This paper analyzes a selection combining (SC) receiver with $L$ branches in wireless communication networks affected by Rician fading and co-channel interference (CCI). A closed-form expression for the moment generating function (MGF) is derived and used to calculate the average bit error probability (ABEP) for non-coherent Binary Frequency Shift Keying (BFSK) and Binary Differential Phase Shift Keying (BDPSK) modulation schemes. Numerical and graphical results are provided to evaluate ABEP performance for varying numbers of diversity branches and Rician κ values. Furthermore, we explore the adoption of Generative Artificial Intelligence (GenAI) techniques to simplify network experimentation and reduce cognitive load. A proof-of-concept implementation is demonstrated through ABEP case study based on the first part of the paper.