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I. INTRODUCTION

II. RELATED SURVEYS

III. LLM FUNDAMENTALS  
A. Model Architecture  
B. LLM Pre-training  
C. LLM Fine-tuning  
D. LLM Inference and Utilization by Prompting  
E. Evaluation Metrics of LLM  
F. LLM Deployment in Telecom Networks  
G. Analyses of LLM Fundamentals in the Telecom Domain  

IV. LLM FOR GENERATION PROBLEMS IN WIRELESS NETWORKS  
A. Motivations of Using LLM-based Generation for Telecom  
B. Domain Knowledge Generation  
C. Code Generation  
D. Network Configuration Generation  
E. Discussions and Analyses  

V. LLM-ENABLED CLASSIFICATION PROBLEMS  
A. Motivations and Classification Capabilities of LLM Models  
B. LLM for Telecom Security and Attack Detection  
D. Image Classification  
F. Discussions and Analyses  

VI. LLM-ENABLED OPTIMIZATION TECHNIQUES FOR TELECOM  
A. Motivations and Optimization Capabilities of LLM  
B. LLM-aided Reinforcement Learning for Network Optimization  
C. LLM as a Black-box Optimizer  
D. LLM-aided Convex Optimization for Telecom  
E. LLM-based Heuristic Algorithm Design  
F. Discussions and Analyses  

VII. TIME SERIES LLM FOR PREDICTION PROBLEMS  
A. Motivations  
B. Pre-training Foundation Models for Zero-shot Prediction  
C. Frozen Pre-trained LLM for Prediction  
D. Fine-tuned LLM Prediction  
E. Multi-modal LLM for Telecom Prediction  
F. Discussions and Analyses  

VIII. CHALLENGES AND FUTURE DIRECTIONS OF LLM-EMPOWERED TELECOM  
A. Challenges of Applying LLM Techniques to Telecom  

IX. CONCLUSION
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