巨量機器裝置通訊(mMTC)在物聯網中為重要的應用場景，是為巨量裝置設計的連結需求、傳輸量小和非經常性傳輸等。mMTC可以使用於LTE-A與NB-IoT的物聯網系統實現，在此兩種系統中，需要傳送資料的每個裝置都必須完成隨機存取程序(Random access)來取得上行資源。隨機存取程序在LTE-A與NB-IoT使用多通道時槽阿羅哈協定(multi-channel slotted ALOHA)，系統的吞吐量會隨著連網的裝置數量增加而下降，此問題是mMTC的一個嚴重瓶頸。
在本篇論文的第一個部分，我們考慮一個LTE-A網路裡有服務不同優先權等級的mMTC服務。如同先前提到的瓶頸，所有裝置的存取層級(access class)都會因為大量裝置的影響，導致低連線成功率(success probability)與高連線延遲(access delay)。為了解決這個問題，我們提出了一套前導碼(preamble)資源分配方式來管理存取層級的優先權，同時滿足其對應的服務品質(QoS)條件。並使用分析模型來估測此方式的效能，和驗證在一定量內的裝置連線下，使用此套資源分配方式可以達成目標。
在本篇論文的第二個部分，我們使用NB-IoT系統，系統中有三種覆蓋增強等級(coverage enhancement level)，其中NB-IoT提出了較為複雜的方式去優化隨機存取程序中參數的設定。對於這個方式，我們的提出了一套方式來設定隨機存取程序的十種參數，且此隨機存取程序在固定的延遲限制下，可令其三種覆蓋增強等級達到最高成功率。優化的參數設定包含覆蓋增強等級的數量、在每一覆蓋增強等級中裝置的最大隨機存取嘗試次數、退後機制的變動量(back off window)與前導碼的數量(preamble)。首先我們提出一分析模型來估算提出方法之性能指標，利用該模型推導出優化策略，並通過計算機模擬和詳盡的資料搜索驗證，證明此方式在各種情況下都能符合要求。
在本篇論文的第三個部分，在NB-IoT系統中，系統使用高重複(repetition)次數來達成高前導碼偵測率(detection probability)的需求。論文中我們探討如此高成本達成需求是否是必要的，透過調整最佳重複次數(repetition)與重傳(retransmission)次數之間的取捨，來達到一定等級的偵測率，並提出一個分析模型來估計性能指標，證明mMTC的過程中，重複次數少，重傳次數高，可以獲得更高的成功機率。

One scenario in internet of things (IoT) is called massive machine-type communication (mMTC). mMTC is commonly characterized with massive number of devices with small and infrequent data transmission. mMTC can be served with cellular technology such as LTE-Advanced (LTE-A) and Narrowband IoT (NB-IoT). In both of them, each device wanting to send their data needs to complete random access (RA) procedure. The RA procedure in LTE-A and NB-IoT is based on multi-channel slotted ALOHA system, which has very low throughput under high load. This is serious bottleneck for mMTC.
In the first part of this thesis, we consider an LTE-A network serving mMTC services with different priorities. With the said bottleneck, low access success probability and high access delay is likely to be experienced by all access classes (ACs), regardless of their priority. To alleviate this problem, we propose a generalized preamble allocation scheme to manage the priority of the ACs and fulfill their QoS requirement. A model is presented to estimate the performance metrics. We demonstrated that the proposed scheme is able to manage the prioritization and fulfill the requirement of the ACs under limited number of available.
In the second part of this thesis, we consider an NB-IoT with up to 3 coverage enhancement (CE) levels. It introduces new level of complexity to optimally configure their RA parameters to yield the optimal performance. For this problem, we propose a method to configure up to 10 parameters in NB-IoT’s RA procedure with up to 3 CE levels to achieve the highest access success probability under certain access delay constrain. The optimized parameters are number of CE levels, maximum number of preamble transmission of each UE, maximum number of preamble transmission in each CE level, backoff window in each CE level, and number of preamble in each CE level. A model is firstly presented to estimate the performance metrics, and is utilized to derive the optimization strategies. The effectiveness of this optimization is verified via computer simulation and exhaustive search, and is proved to work well under various situations.
In the third part of this thesis, we discussed the requirement of a very high detection probability for each transmitted preamble in NB-IoT, which is achieved by considerably high number of repetitions. We doubt that such requirement is required. We investigated the optimal number of repetitions and (re)transmissions to achieve certain requirement of access success probability. A model is firstly presented estimate the performance metrics, and is utilized to identify the preferred situations of ‘repetition’ and ‘retransmission’ technique. We demonstrate that for mMTC, fewer repetitions and more retransmission can achieve higher access success probability.

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