近來感知網路已成為增進目前頻譜使用效率的一個有效方法。然而，感知網路也為目前的無線網路帶來了更多挑戰。在本篇論文中，我們探討在感知網路中多播路由(multicast)與傳送通道分配的問題。我們的目標是找出一組中繼節點與通道分配的方式，而這組中繼節點與通道分配所形成的多播樹(multicast tree)所需要的傳送資源最少。我們證明此問題是一個NP-Complete的問題。因此，我們提出一近似最佳解演算法，並且由此演算法發展一分散式方法。此演算法的設計，主要是針對如何在認知網路中，更有效的利用無線網路的廣播傳送，並進一步的減少多播樹所需要的傳送資源。除此之外，我們也證明使用我們的演算法，產生多播樹所需要的傳送資源是最佳解的常數倍。模擬結果顯示我們所提出方法，與其他多播路由方法比較起來，多播路由所需要的傳輸資源更少，因此可以節省更多的傳輸資源給其他在網路中的傳輸使用。

Cognitive radio networks (CRNs) have become a promising solution to improve the spectrum utilization. However, it also brings up new challenges in wireless networks. In this thesis, we consider the multicast routing and channel allocation problems in cognitive radio networks. The goal is to construct a multicast tree and to assign the transmitting channel of each relay node such that the total transmission cost is minimized. We prove that the minimum multicast tree problem in CRNs is NP-Complete. We propose a centralized approximation algorithm to approach the minimum cost multicast tree in polynomial time. The algorithms are aimed at exploiting the broadcast nature of wireless transmissions and further reducing the total transmission cost of the multicast tree. Based on the centralized algorithm, we develop a decentralized one. The simulation results shows that the total transmission cost produced by our algorithms is less than the cost produced by other multicast routing schemes, which in turn reserves more radio resources for further usage.

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