隨著物聯網和非地面網絡的發展，對高數據傳輸速率和可靠連線的需求顯著增加。低地球軌道衛星星座因其無處不在而被確定用於新的大規模進接網路。在這種情況下，低地球軌道衛星通信將發揮重要作用，為傳統網路無法到達的偏遠地區提供進接和覆蓋。因此，低軌衛星通信可應用於物聯網、遠程醫療、軍事通信、航空等各個領域。儘管是一種可行的替代方案，但這些類型的網路在效能方面仍然受到質疑，尤其是在現實世界通道中的延遲和佇列管理方面。在這些方面，人們提出了關於在衛星網路與地面的聯繫中排隊延誤的新問題。從這個意義上說，現有工作通常忽略了從地面到衛星的真實通道條件下的排隊系統，從而將其分析局限於M/M/1/K系統。在這項研究中，我們使用陸地行動衛星通道模型研究單個衛星到地面鏈路的排隊延遲，其中該通道模型考慮了現實的衛星通道狀態，例如視線 (LoS)、中陰影或深陰影。基於上述機制，我們進一步考慮封包可能具有的屬性，加入了無耐性的特性。此外，我們研究了三種情境：（1）僅有一個衛星節點；（2）考慮兩個衛星節點，其中第一個衛星具有時變的上行鏈路通道狀態，第二個衛星具有時變的下行鏈路通道狀態，且兩者之間為直線傳輸；（3）考慮了一個由三個衛星節點組成的簡化網絡，但只有一個上行鏈路通道和一個下行鏈路通道。首先，我們透過馬可夫鏈推導出所提出模型的狀態平衡方程式。其次，我們使用迭代演算法得出穩態機率分佈和各項效能指標。第三，我們研究了不同參數對於系統有效性的影響。最後，在大部分的研究案例中，解析結果與模擬結果相當接近。

With the rapid development of Internet of Things (IoT) and Non-Terrestrial Networks (NTN), there has been a significant increase in demand for high data transmission rates and reliable connectivity. Low Earth Orbit (LEO) satellite constellations have emerged as a promising solution for enabling massive access networks due to their wide coverage capabilities. Particularly in remote areas where traditional networks are inaccessible, LEO satellite communications can provide vital access and coverage. As a result, these satellite communication systems find applications in diverse fields such as IoT, telemedicine, military communications, and aerospace. Despite their potential, the performance of such networks, especially in terms of latency and queue management in real-world channel conditions, still pose challenges. One of the key issues is the queuing delays experienced in the satellite network-terrestrial links. Existing studies have predominantly focused on analyzing queuing systems using M/M/1/K models, overlooking the unique characteristics and complexities of real channel conditions encountered in the ground-to-satellite links. In this study, we address these limitations by investigating the queuing delay in a single satellite-to-ground link using a land mobile satellite channel model that considers realistic channel conditions, including line-of-sight (LoS), medium shadowing, and deep shadowing. We extend our analysis to incorporate packet attributes and introduce the concept of impatience. Furthermore, we explore three distinct scenarios to assess the performance of the system: (1) a single satellite node, (2) two satellite nodes with time-varying uplink and downlink channel states, and they are connected via an LoS link, and (3) a simplified network comprising three satellite nodes with a single uplink channel and a single downlink channel. To analyze the proposed model, we derive the state balance equations using a Markov chain approach. We employ an iterative algorithm to compute the steady-state probability distribution and evaluate various performance measures. Additionally, we investigate the impact of different parameters on the system's effectiveness. It is worth noting that the analytical results align closely with the simulated results in the majority of the studied cases, validating the accuracy and reliability of our approach.

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