隨著無線行動裝置與多媒體系統的蓬勃發展，人們對於網路服務的需求量與日俱增。為了能夠有效地提升多輸入多輸出(Multiple Input Multiple Output)非正交多重擷取(Non-Orthogonal Multiple Access, NOMA)系統中的頻譜效率(spectral efficiency)，我們研究出一個應用快速吉文斯QR分解(Fast Givens QR Decomposition)做用戶選擇及配對(user selection and pairing)的演算法。透過該演算法，我們替每個叢集(cluster)選出內圈使用者(first user)和外圈使用者(second user)，並將每個叢集對整個系統的總吞吐量(throughput)貢獻最大化。除此之外，為了對抗叢集間干擾(inter-cluster interference)，我們設計了干擾消除(interference cancellation)矩陣。理論分析及模擬結果皆表明，本篇論文所提出的演算法與先前同樣做用戶配對的演算法相比，有較佳的傳輸速率(sum rate)及中斷性能(outage performance)。

With the vigorous development of wireless mobile devices and multimedia systems, people's demand for network services is increasing day by day. To enhance the spectral efficiency of non-orthogonal multiple access (NOMA) in massive multiple input multiple output systems, we propose a user selection and pairing algorithm using Fast Givens based QR Decomposition. Through this algorithm, we select the first user and the second user for each cluster, and each cluster contributes the most to the total throughput of the entire system. In addition, to suppress the inter-pair interference, we design an interference cancellation matrix. Theoretical analyses and computer simulations show that, the proposed algorithm has excellent sum rate and outage performance compared with the traditional user selection and pairing algorithms.

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