面向卫星物联网系统的跨层优化：平衡数据新鲜度与传输效率
C-AoEI-Aware Cross-Layer Optimization in Satellite IoT Systems: Balancing Data Freshness and Transmission Efficiency
AI总结：
本文提出了一种新的跨层优化框架，通过引入C-AoEI度量标准，提升卫星物联网系统中数据新鲜度与传输效率的平衡性能。
摘要：
卫星物联网（S-IoT）面临一个根本性的三重困境：传播延迟、动态衰减和带宽匮乏。虽然分层编码混合自动重传请求（L-HARQ）增强了可靠性，但其回溯解码引入了年龄模糊性，破坏了标准信息年龄（AoI）度量标准，并模糊了数据新鲜度与传输效率之间的关键权衡。为此，我们提出了一种新的跨层优化框架，核心是一个新的度量标准，即跨层误差信息年龄（C-AoEI）。我们推导出C-AoEI的闭合表达式，明确将新鲜度与系统参数联系起来，建立了新鲜度退化与信道动态之间的显式分析联系。在此基础上，我们开发了适用于多GBS场景的分组级编码L-HARQ方案和一个联合优化编码和决策阈值的自适应算法。广泛的仿真显示了我们提出框架的有效性：它实现了比传统方案高31.8%的传输效率和17.2%更低的C-AoEI。该框架还证明了其在小区间干扰和变化信道条件下的鲁棒性，为设计高效、延迟感知的下一代S-IoT协议提供了基础。
英文摘要：
Satellite-based Internet of Things (S-IoT) faces a fundamental trilemma: propagation delay, dynamic fading, and bandwidth scarcity. While Layer-coded Hybrid ARQ (L-HARQ) enhances reliability, its backtracking decoding introduces age ambiguity, undermining the standard Age of Information (AoI) metric and obscuring the critical trade-off between data freshness and transmission efficiency. To bridge this gap, we propose a novel cross-layer optimization framework centered on a new metric, the Cross-layer Age of Error Information (C-AoEI). We derive a closed-form expression for C-AoEI, explicitly linking freshness to system parameters, establishing an explicit analytical connection between freshness degradation and channel dynamics. Building on this, we develop a packet-level encoded L-HARQ scheme for multi-GBS scenarios and an adaptive algorithm that jointly optimizes coding and decision thresholds. Extensive simulations demonstrate the effectiveness of our proposed framework: it achieves 31.8% higher transmission efficiency and 17.2% lower C-AoEI than conventional schemes. The framework also proves robust against inter-cell interference and varying channel conditions, providing a foundation for designing efficient, latency-aware next-generation S-IoT protocols.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
