多重路徑下作調變辨認的研究已經發展了一段時間，大部分主要的系統架構為藉由盲等化器(Blind Equalizer)將信號還原之後，再經由樣式辨認(Pattern Recognition)的方法做出調變種類的判斷。而盲等化器的步進值(step-size or adaptive coefficients)設定是一個決定等化之後還原的信號好壞的因素之一，進而影響調變辨認的正確率。為了提高等化器的效率，選擇一個能兼顧收斂速度與效果的步進值是必要的。但適當的步進值會因為不同的傳輸環境而改變。本論文利用代數方法推出下一次迭代所需要的最佳步進值，避開推導步進值範圍的複雜程序，使用最佳的步進值的等化器其收斂速度也比傳統固定步進值的等化器佳。也讓等化器可以自動適應不同環境變化，解決了通道環境改變之後需要手動重新調整步進值的問題，達到完全「自動」調變辨認的功能。 Automatic modulation classification (AMC) has been developed for a long time. In the presence of multi-path, multi-modulus algorithm, a blind equalization algorithm, is widely used to resolve the multi-path inter symbol interference (ISI). A good blind equalizing ability will result in a good AMC performance. But to my best knowledge, there is few papers mentioning how to choose the suitable step-size automatically to improve the performance of AMC. Optimal step-size multi-modulus algorithm (OS-MMA), which gives a solution to choose the step-size, is derived and applied to automatic modulation classification (AMC) in this paper. The probability of correct classification of AMC with OS-MMA is compared with that of AMC with conventional MMA. And the simulation result shows that AMC with OS-MMA is superior to AMC with conventional MMA.
