Pretrained Large Models in Telecommunications: A Survey of Technologies and Applications

As telecommunications networks become more complex, optimizing performance and predicting traffic are crucial for enhancing customer experience. Pretrained large models (PLMs) based on Transformer architecture have proven effective in processing large-scale structured and unstructured data, making them a promising solution. This paper reviews key technologies and applications of PLMs in telecommunications networks, focusing on data embeddings, model training, and real-time inference. It also explores applications in network performance optimization and fault prediction.