I. INTRODUCTION
A. Intelligent Signal Processing: An Overview
B. State-of-the-art
C. Contributions and Organization of this Paper
II. ARTIFICIAL INTELLIGENCE: BACKGROUND INFORMATION
A. Machine Learning: Preliminaries
B. Deep Learning
C. Federated Learning
III. MODULATION CLASSIFICATION
A. Fundamentals of Modulation Classification
B. State-of-the-Art AMC Methods
C. Summary and Takeaway Points
IV. SIGNAL DETECTION
A. Fundamentals of Signal Detection
B. State-of-the-Art MLDs
C. Summary and Takeaway Points
V. BEAMFORMING AND CHANNEL ESTIMATION
A. Fundamentals of Beamforming
B. State-of-the-Art MLBs
C. Channel Estimation
D. Summary and Takeaway Points
VI. RESEARCH CHALLENGES AND FUTURE DIRECTIONS
A. End-to-End Learning
B. Distributed, Centralized, or Hybrid Learning
C. Model Compression and Acceleration
D. Dataset Generation and Unification
E. Universality and Practicality
F. Deep Semi-supervised and Active Learning
G. Standardization and Open-Source Activities
H. Support for New Services
VII. CONCLUSION