LTE-MTC (Machine-Type Communication) 專為物聯網應用所設計的 LTE 網路技術[1]，相較於傳統人對人(Human-to-Human, H2H)，MTC通訊具備幾項特點，例如：極低的電耗量、較低的移動性、較低的資料傳輸量，及非經常性資料傳輸等。MTC 裝置的數量預計比傳統 H2H 裝置大上許多，現有提供 H2H 通訊所設計之標準，用在提供 MTC 通訊服務時，行動通訊網路架構的各個階層都可能面臨頗為嚴重的壅塞。
本論文主題研究在於，當大量MTC裝置同時嘗試與基地台連結，會發生大量的隨機存取碰撞並影響網路服務品質，並根據競爭式(裝置競爭)及非競爭式(基地台指派)共計64個Preamble讓裝置競爭及指派，透過動態調整Preamble以舒緩壅塞及封包延遲並提升網路服務品質，所謂動態調整是透過基地台Preamble使用程度計算使用率並估算承載量，透過承載量提出二段式及三段式動態調整方式，評估是否動態調整Preamble，依據調整的Preamble數量修改基地台SIB參數並在每個週期廣播(Paging)給裝置，有效分配Preamble讓裝置競爭及指派，降低裝置碰撞率到達提升效能目的。
模擬部份利用不同程度的MTC裝置數量及P隨機存取機率，從模擬結果得知提出的動態調整方法較不動態調整且在裝置多的情況下，可有效減少一半以上的隨機存取時間，詳細結果可參照第四章模擬結果與討論。

LTE-MTC (Machine-Type Communication) is designed for IoT applications, compared to traditional Human-to-Human (H2H); MTC communication has several features, such as: extremely low power consumption, low mobility, lower data transmission, and non-recurring data transmission. MTC devices are more than traditional H2H devices in quantity. When the standards of MTC communication services are used for H2H communication, each layer of the architecture in mobile communication network may face the serious congestion problem.
The main research of this thesis is that a large quantities of random access collisions will occur and cause the impacts on the quality of network service when a large amounts of MTC devices try to connect with the base station at the same time; allocating 64 preambles to compete with different devices through the contention based (devices competition) and contention-free based (base station assignment). By dynamically adjusting preambles to ease the congestion and packet delay to improve the service quality of network. The so-called “dynamic adjustment” is to calculate the usage rate and estimate the carrying capacity through the usage level of preambles in base station. Two-stage and three-stage dynamic methods are proposed to evaluate whether to adjust the preambles dynamically through the carrying capacity. Then, according to the adjusted quantities of preambles, SIB parameters are modified in the base station and eNB broadcasts (pages) to the MTC devices in each cycle. Allocating preambles effectively to let the devices to compete and be assigned, eventually, it could reduce devices collision in order to improve the system performance.
The simulation part utilizes different level of MTC devices and probability of P random access. It is known from the simulation results that proposed dynamic adjustment method can reduce the random access time effectively by more than half of the random access time in which devices without dynamic adjustment. Please refer to Chapter 4 for simulation results and discussion.

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