Beyond the "G" Frontier: A Time Traveler's Century-Long Vision for Wireless Intelligence

TL;DR

This work reframes wireless evolution as a curvature-driven process governed by the Information–Curvature Efficiency Law (ICEL). It unifies physics, biology, and society by introducing curvature-aware capacity, a bio-spectral information economy, and quantum–thermodynamic computation within a single framework. Key contributions include a curvature-weighted Landauer limit, governance and ethics informed by curvature metrics, and a multiscale life–information geometry that ties genomic, neural, and ecological curvature into a common optimization. The implications point to a sustainable, planet-scale information ecology where communication, cognition, and ecology coevolve along a shared geometric manifold, culminating in a state of communion that preserves existence by keeping curvature flat.

Abstract

This article travels one century into the future--from 2025 to 2125--through the analytical lens of the Information--Curvature Efficiency Law (ICEL). It contends that wireless evolution will not proceed through incremental generations such as 6G or 7G, but through a curvature-managed integration of electromagnetics, biology, thermodynamics, and cognition. The resulting infrastructure will constitute a global ecology of self-aware information flow, where geometry and communication converge to sustain both technological and biological life.

Figures (11)

• Figure 1: Graphical Abstract — Curvature as the Fifth Invariant. Three‑dimensional efficiency surface $\eta(C)$ in Energy–Information–Curvature space, summarizing the Information–Curvature Efficiency Law (ICEL) across physics, biology, and society.
• Figure 2: Flat vs curved capacity surfaces. Axes: signal‑to‑noise ratio (S/N), bandwidth $B$, and capacity ratio $C/C_{\mathrm{ICEL}}$. Demonstrates how curvature modifies channel capacity via $\Delta C=\lambda C/(1+C^2)$.
• Figure 3: Curvature‑controlled RAN simulation grid. Heat map of cell load vs curvature gradient with energy consumption overlay, demonstrating thermodynamic stability under adaptive curvature feedback.
• Figure 4: Molecular curvature tensor map of micro‑electric field $E_{\text{micro}}$. Color represents magnitude of biological curvature $C_b$. Visualizes bio‑plasmonic membrane patterns supporting $\mathbf{C}_b=\nabla\times(\nabla\times\mathbf{E}_{\text{micro}})$.
• Figure 5: Hierarchical Bio–Spectrum Network (IBS). Nodes represent cells, swarms, and satellites; edge weights encode curvature coherence $\chi$. Depicts system‑level coupling of biological and digital curvature flows.