6G network design puts AI at the center of spectrum, routing, and fault management

This report summarizes research on embedding AI into 6G networks, covering expected capabilities (throughput, latency, reliability), the application of ML/DL/federated learning across network layers, security risks such as data poisoning and model inversion, mitigation strategies (adversarial training, Byzantine-tolerant aggregation, blockchain for audit), and engineering constraints like energy, hardware, and interoperability.