Using cyclostationarity to detection and identification in OFDM system for Cognitive Radio Network

因應著數位時代的來臨，無線網路變成通訊的主要方式，無線產品也隨之激增，而有限資源的頻譜也隨著無線產品的增加，陷入了缺乏頻譜的窘境，故感知型無線網路偵測周圍環境未被充分使用的頻寬進而使用，可解決這個問題。 在感知型網路當中，偵測頻譜是一個主要討論的課題，可以說是決定感知型網路技術能否成功的關鍵之一，傳統上使用能量檢測器進行頻譜感應(Spectrum Sensing)，雖然能量檢測器簡單且感應速度快，但有許多的缺點仍需要去解決，故在此篇論文使用人工製造出的信號均有的週期性循環特性來進行信號的偵測及辨識，利用正交分頻多工系統中本身具有的特性，進而達到有效率的偵測環境中未被使用到的頻譜，主要的概念是使用正交分頻多工系統中的循環字首(Cyclic Prefix)和週期出現的領航訊號樣式(Pilot Pattern)來進行更精準的偵測訊號。 傳統上使用週期性循環特性進行辨識信號需要相當高的複雜度，此篇論文以另一種思維方式判斷信號是否存在，大幅的降低辨識的複雜度，故可用線性成長幅度不大複雜度的演算法，進而達到更精準的訊號偵測及辨識。Because the digital era comes,wireless communication is the main communication way,and the wireless product is also increase rapidly,however,the spectrum is limited,so we suffer the scarcity spectrum case,fortunately,Cognitive Radio Network (CRN) can slove this problem,CRN can obtain environment parameters to detect the spectrum is vacant or not. In CRN,spectrum sensing is a major topic,we can say spectrum sensing is one of the keys of technique to decide CRN’s success, traditionally,using energy detection to spectrum sensing,although energy detection is simple and sensing period is fast,but still have lots of drawbacks to slove,so in this paper using man-made signal’s cyclostationarity to detection and identification signal,using Orthogonal Frequency Division Multiplexing(OFDM) system feature to efficiently detect unused spectrum,the major principle is using OFDM system’s Cyclic Prefix(CP) and periodic present Pilot Pattern to accurately detection. Traditionally,using cyclostationarity to identification need quite high complexity,so in this paper use the other way to decide signal is present or not,let the complexity quit lower,so we use linearly increase complexity algorithm,get the better signal detection and identification