ChatGPT-Aided QoS Estimation Le eraging Outage Probability of Mobile Networks Limited by α-η-µ Fading and α-η-µ Co-channel Interference

In this paper, we analyze the performance of wireless communication system affected by α-η-μ fading in the presence of α-η-μ co-channel interference (CCI) for the receiver with selection combining (SC) with L branches. In the paper, a closed-form expression for the system outage probability (Pout) of the ratio of the received signal and interference (SIR) are derived. Obtained results can be used in performance analysis of wireless communication system which uses diversity technique to reduce fading effects in fading channels. On the other side, in the second part of the paper, we investigate the potential of trending ChatGPT based on Large Language Mode (LLM) for task of QoS estimation, taking into account Pout among model inputs. Finally, the proposed method is compared to traditional machine learning algorithms using Weka in Java programming language.