未來，因為自動互連裝置數量快速成長，物聯網將會是第五代行動通訊無線網路系統中不可或缺的一部分。物聯網最主要的挑戰是大量連接的議題。論文中我們降低符際與載波間干擾效應為了提高在時頻分散通道中物聯網裝置可負荷的數量利用最佳化雙正交分頻多工技術的效能。雙正交分頻多工技術是發明來降低干擾透過一個有彈性的訊號波形設計，我們採用具有良好特性降低干擾的B 樣條和高斯波形和使用名為典型高柏視窗計算接收波形。特別是我們最佳化雙正交分頻多工高斯波形利用最小化尾模稜函數。模擬結果顯示所提出的雙正交分頻多工勝過傳統正交分頻多工在干擾能量、訊號干擾比及物聯網裝置的負載量於時頻分散通道。本論文提出的雙正交分頻多工不僅達到降低干擾，並同時增加系統可支援的裝置數量。

In future, Internet-of-Thing (IoT) will be the indispensable part of development of 5G wireless communication system due to rapid growth of devices with an ability to communicate autonomously. The major challenge is massive connection issue. In this thesis, we reduce intersymbol interference (ISI) and intercarrier interference (ICI) for enhancing the number of IoT devices in high mobile environment by optimizing the performance of Biorthogonal Frequency Division Multiplexing (BFDM). BFDM is invented to reduce the interference through a flexible design of the signal pulse shaping. We apply B-splines and Gaussian pulse for pulse shape which have good properties to reduce ISI/ICI and use an algorithm named canonical Gabor tight window to calculate receive pulses. In particular, we optimize Gaussian pulse in BFDM by minimizing the tail of the ambiguity function. Simulation results show that the proposed BFDM outperforms the conventional OFDM in ISI/ICI power, SIR and the IoT devices load in time-frequency dispersive channels. BFDM not only achieves the reduction of interference, but also increases the number of devices which system could support.

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