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.

翻译：多运营商低轨巨型星座间的动态频谱共享对于共存至关重要，但现行策略几乎完全聚焦于干扰抑制，地理公平性问题在很大程度上未被解决。本研究探讨传统动态频谱共享方法是否会无意间加剧农村数字鸿沟。通过采用符合3GPP标准的非地面网络大规模仿真，并结合地理分布用户场景，我们系统评估了标准分配策略。结果揭示了一种显著且持续存在的结构性偏差：信噪比优先调度导致城乡接入差异达1.65倍，使具有有利卫星几何位置的用户获得特权。反直觉的是，增加系统带宽反而会扩大而非缓解这一差距——当资源扩展时，差异率从1.0倍上升至1.65倍。为纠正此问题，我们提出FairShare——一个轻量级、基于配额的框架，用于保障地理公平性。FairShare不仅逆转了偏差，实现了正向差异比Δ_geo = 0.72倍，还将调度器运行时间降低了3.3%。这表明算法公平性可以在不牺牲效率或复杂度的前提下实现。本研究为监管机构提供了用于审计公平性的诊断指标，以及适用于下一代卫星网络的公平频谱治理实践方案与可执行机制。