FairShare: Auditable Geographic Fairness for Multi-Operator LEO Spectrum Sharing

2026-01-14

AI Summary

This study addresses the neglect of geographic fairness in existing dynamic spectrum sharing mechanisms for low Earth orbit (LEO) satellite networks, which exacerbates the urban–rural digital divide. Through large-scale 3GPP-compliant non-terrestrial network simulations, the work reveals—counterintuitively—that increasing bandwidth can widen the access disparity between urban and rural users. To mitigate this, the authors propose a lightweight, auditable quota-based fair scheduling framework that incorporates a novel geographic fairness metric, Delta_geo. This framework simultaneously preserves spectral efficiency and computational simplicity while reversing the urban–rural access gap to 0.72× its original magnitude and reducing scheduler runtime by 3.3%. The results offer regulators an actionable fairness governance mechanism alongside a verifiable auditing tool.

Technology Category

• Game Theory and Economic Paradigms: Fair Division
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search

Application Category

• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

Dynamic spectrum sharing (DSS) among multi-operator low Earth orbit (LEO) mega-constellations is essential for coexistence, yet prevailing policies focus almost exclusively on interference mitigation, leaving geographic equity largely unaddressed. This work investigates whether conventional DSS approaches inadvertently exacerbate the rural digital divide. Through large-scale, 3GPP-compliant non-terrestrial network (NTN) simulations with geographically distributed users, we systematically evaluate standard allocation policies. The results uncover a stark and persistent structural bias: SNR-priority scheduling induces a 1.65x urban-rural access disparity, privileging users with favorable satellite geometry. Counter-intuitively, increasing system bandwidth amplifies rather than alleviates this gap, with disparity rising from 1.0x to 1.65x as resources expand. To remedy this, we propose FairShare, a lightweight, quota-based framework that enforces geographic fairness. FairShare not only reverses the bias, achieving an affirmative disparity ratio of Delta_geo = 0.72x, but also reduces scheduler runtime by 3.3%. This demonstrates that algorithmic fairness can be achieved without trading off efficiency or complexity. Our work provides regulators with both a diagnostic metric for auditing fairness and a practical, enforceable mechanism for equitable spectrum governance in next-generation satellite networks.

Problem

• geographic fairness
• spectrum sharing
• LEO constellations
• digital divide
• multi-operator

Innovation

• geographic fairness
• dynamic spectrum sharing
• LEO mega-constellations
• FairShare
• non-terrestrial networks