AI-Driven Blockchain Framework for Optimizing Latency, Reliability, and Energy-Efficient QoS in 5G/6G Mobile Networks

Abstract

The 5G and beyond-6G next-generation wireless networks require ultra-low latency, ultra-high reliability, and ultra-low power consumption in order to accommodate mission-critical and massive-scale IoT cases. Classical centralized network control cannot fulfill such high-quality QoS needs, particularly under explosive data expansion and device proliferation. This paper outlines a new AI-enabled blockchain architecture that collaborates edge computing with federated learning for intelligent control of network resources, yet exploits blockchain's distributed trust for added security and confidentiality. In this paper an architecture in which AI agents at the edge of a network dynamically adjust resource control (spectrum, compute, power) for minimum latency and power consumption, and maximum reliability, such that decisions and information exchange are immutably stored on a blockchain ledger for security and visibility is described. A reinforcement learning-based algorithm with adaptive power management is developed to orchestrate base station activity and edge service placement, guided by smart contracts that enforce fair and reliable resource sharing across the network. We evaluate the framework against state-of-the-art approaches through simulations. The results demonstrate that our approach significantly reduces end-to-end latency and network energy consumption while improving reliability (packet success rates and outage probability) compared to conventional methods. The federated learning mechanism integrated helps maintain data privacy for users while not compromising model quality. In general, this AI-blockchain configuration offers a scalable, secure QoS administration paradigm for 5G/6G networks, which helps pave the way for intelligent, automated future wireless networks.