所選用的系統模型為使用多頻帶 (Multi-Band) 傳輸的超寬頻系統 (Ultra-Wide Band)，每個頻帶內除了使用正交分頻多工（OFDM）的技術來傳輸外還加上了多重進接 (Multiple Access) 的技術。所以就等同於在每個頻帶內使用多載波分碼多重進接 (MC-CDMA) 的方式來傳輸資料。而在超寬頻系統中容易受到窄帶雜訊干擾 (Narrow
Band Interference，NBI) 的問題也已經在研究上受到重視。

我們將使用一些在接收端具有窄帶雜訊干擾抑制的方法，如Robust Min-Max M-estimator 或是具有窄帶雜訊干擾消除的方法，如Consecutive Mean Excision (CME)、Forward Consecutive Mean Excision (FCME)、Least Median of Square (LMedS)、Reweighted Least Square (RLS) 等方法來解決此問題，並比較這些方法所需要的運算複雜度，進而修改CME、FCME、LMedS、RLS等方法成為複雜度較低的easyCME、easyLMedS、easyRLS，以及事先根據LMedS進而降低複
雜度的方法Max Subcarrier Power (MSP)。

並且根據系統的雜訊模型來分析easyLMedS0、easyCME這些方法對超寬頻系統的子載波是否被窄帶雜訊干擾的偵測機率 (Detection probability) 與誤警機率 (False alarm probability)，並利用電腦模擬來驗證理論分析的結果。並且也可以進而利用窄帶雜訊干擾偵測的方式來偵測對超寬頻系統造成干擾的通信技術是否在運行當中。

最後我們利用電腦模擬的結果可以看出在受到窄帶雜訊干擾的情況下，CME、FCME、 easyCME在不同的演算法參數設定下的效能差別並找出適合系統的演算法參數設定。以及利用 LS、Robust、CME、FCME、LMedS、easyLMedS、 easyRLS、 easyCME、MSP這些方法所得到的系統錯誤率。並利用電腦模擬分析結果證明
easyCME為CME與FCME的上界 (Upper Bound)。模擬結果為easyCME與MSP在錯誤率的表現上都優於其他方法。而easyLMedS的方法也明顯優於one LMedS。easyCME也優於CME與FCME。這些方法大抵上錯誤率由高至低的順序約為one LMedS、FCME、CME、easyLMedS、easyCME、MSP。而Robust Mini-Max M-estimator在窄帶雜訊干擾能量小時略優於上述部分方法，因為此時LS並沒有受到非常嚴重的影響，所以Robust Mini-Max M-estimator還是能夠達到抑制窄帶雜訊干擾的目地。而當窄帶雜訊干擾能量大時，Robust Mini-Max M-estimator明顯沒有在能力有限的遞迴次數裡，來抑制過
大的窄帶雜訊干擾。

In this thesis, the multiband (MB)-orthogonal frequency division multiplexing (OFDM) ultra-wide band (UWB) system is investigated. The symbol of each user is spread by a spreading code to all subcarriers. Thus, the system model employed is equivalent to that of a multicarrier (MC)-code division multiple access (CDMA). Many researchers have paid attention to the problem of narrowband interference (NBI) cancellation on UWB system.

Several techniques are employed at the receiver to do NBI suppression or cancellation. The NBI suppression technique is robust mini-max M-estimator. The NBI cancellation techniques are consecutive mean excision (CME), forward consecutive mean excision (FCME), least median of square (LMedS) and reweighted least square (RLS). We improve the methods of CME, FCME, LMedS and RLS to from easyCME, easyLMedS, easyRLS, and Maximum subcarrier power (MSP). We also compare the complexities of the estimators mentioned above.

The outlier detection probability and false alarm probability of easyLMedS and easyCME are analyzed according to the noise model. Computer simulations are run to verify the analytical. We can also use outlier detection methods to detect if NBI exists.

From computer simulation we can find the appropriate parameters of CME and FCME and prove that the performance of easyCME is the upper bound of those of CME and FCME. From the bit error rate of computer simulations, the following conclusions are made. First, easyCME and MSP are better than other estimators. Secondly, EasyLMedS is batter than LMedS. Thirdly, easyCME is better than CME and FCME. Those estimators on BER curves sequenced in the descending order are LMedS, FCME, CME, easyLMedS, easyCME and MSP. When NBI power is not too large, robust mini-max M-estimator
still can suppression NBI. But when NBI power is too large, robust mini-max M-estimator can not control NBI well.

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