Information-Theoretic Foundations for 6G and Beyond: Fundamental Limits and Tradeoffs

Next-generation 6G and beyond (6GB) networks are expected to meet at least 10x higher performance targets compared to existing 5G networks and support a much wider variety of use cases. However, these targets and use cases cannot be supported merely by brute-force hardware and spectrum scaling. Meeting simultaneous and often competing demands for extreme throughput, sub-millisecond latency, massive machine-type connectivity, zero-energy operation, and provable security, privacy, and robustness pushes wireless systems directly against their fundamental limits. Navigating these inherent tradeoffs requires a return to rigorous information-theoretic principles to guide practical system architecture and protocol design.Over the past few decades, information theory has provided the definitive mathematical framework for data compression, channel capacity, and network optimization. Today, its tools are essential for answering pressing architectural and operational questions in 6G and beyond networks: unifying sensing and communication under shared hardware, and energy and power budgets, formalizing semantic and goal-oriented transmission beyond classic bit-level fidelity, establishing finite-blocklength bounds for mission-critical low latency, and characterizing security, privacy, and resilience under adversarial conditions.This Research Topic serves as a multidisciplinary platform connecting pure information theorists with communication system architects and signal processing engineers. We welcome contributions that establish fundamental bounds, develop capacity-approaching algorithms, explore information-theoretic insights into machine learning for communication, or evaluate practical implementations and protocols tailored to 6G and beyond scenarios.Areas of interest include, but are not limited to:• Fundamental Limits and Multi-User Networks: Multi-user and multi-terminal capacity regions, broadcast and interference management, network coding, and non-asymptotic/finite-blocklength analysis.• Semantic and Goal-Oriented Communications: Information-theoretic formulations of semantic entropy, rate-distortion-perception, task-oriented transmission, and AI-native communication bounds.• Integrated Sensing and Communications (ISAC): Unified performance bounds, sensing-throughput tradeoffs, estimation-rate interactions, and waveform design and optimization.• Ultra-Reliable Low-Latency Communication (URLLC): Latency-reliability-energy tradeoffs, finite-blocklength coding schemes, and statistical QoS bounds for mission-critical networks.• Provable Security, Privacy, and System Resilience: Physical-layer security, wiretap channel models, covert communication, differentially private data transmission, and adversarial robustness.• Information Theory for/with Machine Learning: Generalization bounds in communications, deep learning-aided coding and decoding, and neural compression limits.• Quantum Information and Emerging Physical Paradigms: Quantum channel capacity, quantum key distribution, entanglement-assisted communications, and information-theoretic analysis of reconfigurable intelligent surfaces (RIS) and stacked intelligent metasurfaces (SIM).• Energy-Constrained and Green Communications: Information-theoretic limits on energy harvesting, ambient backscatter, and extreme power-efficient protocols. Topic editors: Samar Agnihotri, Kenneth W. Shum, Alexandros-Apostolos A. Boulogeorgos, Pooja Vyavahare Source: https://www.frontiersin.org/research-topics/85904/information-theoretic-foundations-for-6g-and-beyond-fundamental-limits-and-tradeoffs