Responsible Wireless Intelligence: Foundations of a New Cross-Layer Paradigm

Abstract

Wireless communication systems are evolving beyond information transmission toward wireless intelligence: systems that communicate, sense, learn, infer, and increasingly support autonomous decisions and actions. Advances in integrated sensing and communication (ISAC), artificial intelligence, semantic communications, and emerging quantum technologies are accelerating this evolution. However, increased awareness and autonomy make conventional communication-centric design objectives insufficient. Future systems must balance communication and sensing performance with robustness, privacy, security, energy efficiency, electromagnetic exposure, sustainability, and trust, calling for a fundamental reconsideration of how wireless systems are conceived, designed, and evaluated.

This article introduces Responsible Wireless Intelligence (RWI) as a new cross-layer paradigm that elevates responsibility from a set of system constraints to a fundamental design principle spanning physical modeling, information theory, signal processing, artificial intelligence, and application-driven design. We establish the foundations of RWI by showing how physics and information theory define the limits of wireless intelligence, how cross-layer signal processing approaches these limits through model-based optimization and adaptive learning, and how ISAC, semantic communications, privacy-preserving learning, and emerging quantum technologies integrate within this broader framework. RWI thereby exposes fundamental tradeoffs among communication, sensing inference, privacy, resource consumption, and societal objectives, opening a new research agenda on limits, metrics, algorithms, and cross-layer optimization for wireless systems that communicate, sense, learn, reason, and act responsibly.