Explains deep learning methods for reducing access, transmission, and processing latency
Discusses algorithm unrolling and multiarmed bandit for minimizing access latency
Provides task-oriented compression techniques to reduce transmission latency
Integrates graph neural networks and multi-agent reinforcement learning for processing latency optimization
Includes simulation setup, benchmarking algorithms, and downloadable code
Summarized by Shop
Machine Learning for Low-Latency Communications presents the principles and practice of various deep learning methodologies for mitigating three critical latency components: access latency, transmission latency, and processing latency. In particular, the book develops learning to estimate methods via algorithm unrolling and multiarmed ban