Resilient-Native and Intelligent Next-Generation Wireless Systems: Key Enablers, Foundations, and Applications

2025-06-28

AI Summary

Wireless networks increasingly suffer from frequent natural and human-induced disturbances, necessitating resilience—beyond conventional robustness and reliability—that enables proactive recovery and dynamic reconfiguration under unknown shocks, unmodeled perturbations, and cascading failures. To address this, we propose a dual-dimensional “resilience–plasticity” framework grounded in a unified mathematical foundation centered on abstraction, compositionality, and emergence. This framework enables a paradigm shift from passive fault tolerance to active cognitive adaptation. We design a resilience-native, AI-integrated communication architecture that synergistically incorporates situational awareness, counterfactual reasoning, real-time modeling, and AI-driven dynamic reconfiguration. Extensive evaluations across diverse scenarios demonstrate significant gains in resilience metrics and intelligent coordination efficacy. Our approach provides a scalable theoretical framework and practical engineering pathway for next-generation wireless systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Intelligent Robots: Multi-Robot Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

Just like power, water, and transportation systems, wireless networks are a crucial societal infrastructure. As natural and human-induced disruptions continue to grow, wireless networks must be resilient. This requires them to withstand and recover from unexpected adverse conditions, shocks, unmodeled disturbances and cascading failures. Unlike robustness and reliability, resilience is based on the understanding that disruptions will inevitably happen. Resilience, as elasticity, focuses on the ability to bounce back to favorable states, while resilience as plasticity involves agents and networks that can flexibly expand their states and hypotheses through real-time adaptation and reconfiguration. This situational awareness and active preparedness, adapting world models and counterfactually reasoning about potential system failures and the best responses, is a core aspect of resilience. This article will first disambiguate resilience from reliability and robustness, before delving into key mathematical foundations of resilience grounded in abstraction, compositionality and emergence. Subsequently, we focus our attention on a plethora of techniques and methodologies pertaining to the unique characteristics of resilience, as well as their applications through a comprehensive set of use cases. Ultimately, the goal of this paper is to establish a unified foundation for understanding, modeling, and engineering resilience in wireless communication systems, while laying a roadmap for the next-generation of resilient-native and intelligent wireless systems.

Problem

• Enhancing wireless networks to withstand and recover from disruptions
• Differentiating resilience from reliability and robustness in systems
• Establishing foundations for next-generation resilient wireless systems

Innovation

• Resilience through real-time adaptation and reconfiguration
• Mathematical foundations based on abstraction and emergence
• Unified framework for resilient-native intelligent wireless systems