在感知無線電網絡（CRNs）中，次用戶（SUs）必須有效地在多個通信通道中發現彼此，同時避免對主要用戶（PUs）的干擾。傳統的多通道交會算法主要專注於使一對次用戶找到共同通道，而沒有明確考慮底層網絡拓撲。在這篇論文中，我們擴展了框架，明確納入網絡拓撲，引入了多通道拓撲發現的問題(multichannel topology discovery problem)。我們提出了一種新穎的向前替換的偽隨機掃描算法 (pseudo-random sweep algorithm with forward replacement)，旨在最小化連續不成功碰面的嘗試之間的相關性，從而顯著減少發現時間（ETTD）。此外，我們引入了一種黏合策略 (stick-togehter strategy)，根據部分已知的信息動態同步用戶的跳頻序列，進一步提高發現效率。另外我們也引入了一種混合策略 (hybrid strategy)，該策略在個別通道選擇和黏合方法之間交替，以優化拓撲發現過程。廣泛的模擬結果驗證了我們的理論分析，顯示出所提出的算法在性能上大幅優於傳統（序列）掃描方法。

In Cognitive Radio Networks (CRNs), secondary users (SUs) must efficiently discover each other across multiple communication channels while avoiding interference from primary users (PUs). Traditional multichannel rendezvous algorithms primarily focus on enabling pairs of SUs to find common channels without explicitly considering the underlying network topology. In this thesis, we extend the rendezvous framework to explicitly incorporate network topology, introducing the multichannel topology discovery problem. We propose a novel pseudo-random sweep algorithm with forward replacement, designed to minimize correlation between consecutive unsuccessful rendezvous attempts, thereby significantly reducing the expected time-to-discovery (ETTD). Additionally, we introduce a stick-together strategy that dynamically synchronizes user hopping sequences based on partially known information, further enhancing discovery efficiency. We also present a hybrid strategy that alternates between individual channel selection and the stick-together approach to optimize the topology discovery process. Extensive simulation results validate our theoretical analysis, demonstrating that the proposed algorithms substantially outperform conventional (sequential) sweep methods.