第五代移動通信技術（5G）是目前無線通信領域的重大里程碑，為了支援萬物聯網、智能城市等等的願景，對於在有限資源下如何將使用者數增加的研究也就順勢而生，因此就有了非正交多址（Non-Orthogonal Multiple Access, NOMA）的出現。NOMA與傳統的正交多址(Orthogonal Multiple Access, OMA) 最大的差別是在於NOMA是使用非正交的方式將資源分配，在同一時間和頻率資源上去支援更多的使用者，作為代價，在接收端必須使用更複雜的計算來處理多用戶的訊號。

和目前主流在Power-Domain進行NOMA的方案不同，在本篇論文中是以Code-Domain 來做NOMA方案的設計，使用Walsh code的 DS-CDMA(Direct-Sequence Code Division Multiple Access)與OFDM-CDMA(Orthogonal frequency-division multiplexing CDMA)為基礎，場景分別設定為上行(uplink)與下行(downlink)，透過與 Walsh code性質相似的碼，和Walsh code組合成新的展頻碼(在此稱為擴展華氏碼, Extended Walsh Codes)，進行Code-Domain 的NOMA方案討論，並且在接收端使用改良後的梯度搜尋的方法，來達成多用戶偵測。

本文的內容主要包含四個部分。第一部分是介紹傳統的DS-CDMA及OFDM-CDMA的原理以及在瑞利衰落通道下的零強制（Zero-Forcing, ZF）和最小均方誤差（Minimum Mean-Square Error Equalization, MMSE）的等化方法。第二部分是針對Code-Domain NOMA方案的展頻碼的設計與系統的公式推導及討論。第三部分是討論梯度搜尋演算法，梯度搜尋演算法是以差分度量為基礎，最初是為了改善多輸入多輸出(Multiple-Input Multiple-Output, MIMO)系統的偵測，使其接近最大概似(Maximum Likelihood, ML)偵測的結果，同時也可以在錯誤率性能與計算複雜度之間達成平衡，在本文中將其應用於此NOMA方案中。最後一部分則是系統模擬，對本文所提到的系統進行模擬及分析討論。

Non-orthogonal Multiple Access(NOMA) is one of the candidate technologies for 6G, including power-domain NOMA, code-domain Low Density Signature(LDS) NOMA, etc. This thesis belongs to the code domain non-LDS NOMA. In this thesis, we propose two NOMA schemes, Direct-sequence NOMA(DS-NOMA) and Multi-carrier NOMA(MC-NOMA), based on traditional DS-CDMA and OFDM-CDMA. Therefore, the scenario of power allocation is not considered. Three extended Walsh codes are used for spreading code in the system, composed of Walsh codes and new spreading codes similar to Walsh codes (mutually orthogonal but not orthogonal to Walsh codes), thus retaining some orthogonal properties.

In the receiver, as power allocation is not considered, we reference the Gradient Search Algorithm (GSA) to detect and improve its search method. Gradient search was originally developed as one of the methods to approach Maximum Likelihood (ML) detection in Multiple-Input Multiple-Output(MIMO) systems. However, its impractical computational complexity hindered its implementation in practice. Therefore, a simplification was pursued to strike a balance between computational complexity and performance, referred to as GSA. As the signal model of MIMO systems bears some resemblance to the NOMA proposed here, we aim to apply GSA to the receiver and further enhance it to improve bit error rate(BER) while maintaining computational efficiency.

Finally, we conduct simulations using Monte Carlo methods, assuming known channel State Information(CSI) and synchronized. With an additional 25% increase in users, the bit error rate(BER) of DS-NOMA can approach the orthogonal scenarios, while MC-NOMA can achieve BER results similar to those in orthogonal scenarios. Moreover, the improved search method, with minimal increase in computational complexity compared to previous methods, effectively reduces the BER at the receiver.

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