由於無線通訊的需求不斷增加，智慧反射面被視為一項輔助訊號傳輸並解決傳輸量問題的潛力技術，智慧反射面是由許多反射元件均勻排列組成的面板，每個反射元件會調整入射訊號的振幅和相位並反射訊號，幫助使用者獲得更好的收訊品質。現有文獻指出不規則智慧反射面提升收訊強度的潛力，且反射元件間存在的互耦合對於智慧反射面的訊號傳輸呈負面影響，如何調整不規則智慧反射面上反射元件的位置以降低互耦合，進而改善使用者的收訊品質是本篇論文的主要目標。許多現有文獻使用啟發式演算法研究不規則智慧反射面的相關問題，但由於啟發式演算法無法保證其解的最佳性，因此本論文選擇使用元啟發式演算法；因為陣列狀的智慧反射面可以透過零和一表示每個反射元件的使用與否，適合對應至由零和一組成的基因演算法染色體，因此本論文提出設計智慧反射面拓樸的單目標和多目標基因演算法。除了對互耦合進行優化外，傳播通道也是影響訊號強度的關鍵因素，故所提演算法分別或同時優化互耦合和通道，亦即透過交配、突變等機制尋找低互耦合、高品質通道或是兩者兼具的智慧反射面拓樸；此外，所提多目標基因演算法導入訊號主瓣的概念改良反射元件被選擇使用的機率，越接近訊號主瓣的反射元件被選擇使用的機率越高，透過此方式，所提多目標基因演算法可以更快速地找到優質的智慧反射面拓樸，模擬結果顯示，本論文提出的多目標基因演算法設計之不規則智慧反射面拓樸可顯著改善使用者的收訊品質。

With the uninterrupted wireless communication demands, intelligent reflecting surface (IRS) is regarded as a promising technology that can be used to assist signal transmission and to address transmission volume problems. IRS is a planar surface consisting of a large number of passive reflective elements. Each reflective element adjusts the amplitude and phase of the incident signal and reflects the signal, so that user equipment (UE) can obtain a better received signal. Existing literatures pointed out that the irregular IRS can strength UE’s received signal, but the mutual coupling between reflective elements has a negative impact. How to determine the position of the reflective elements on an irregular IRS for reducing mutual coupling effect and improving received signal is the main goal of this thesis. Many existing literatures use heuristic algorithms to solve the problems of irregular IRS. However, heuristic algorithms cannot guarantee the optimality of their solutions, thereby this thesis utilizes meta-heuristic algorithms. Because the topology of irregular IRS can intuitively use 0 or 1 to represent selected and unselected elements, which is quite similar to chromosomes in genetic algorithm (GA), single-objective and multi-objective genetic algorithms (MOGA) are proposed to design irregular IRS topology. In addition to mutual coupling, propagation channel is also vital to received signal. The proposed algorithm optimizes mutual coupling and channels separately or simultaneously. Through crossover, mutation and other operations to find an irregular IRS topology with low mutual coupling, high-quality channels or both at the same time. In addition, the proposed MOGA introduces the concept of the main lobe to modify the probability of the element being selected. The closer the element to the main lobe, the higher the probability of being selected. Therefore the proposed MOGAs can find better IRS topology more quickly. Finally, simulation results show that the proposed MOGA algorithm is capable of finding an irregular IRS topology with superior received signal for UEs compared with other methods.

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