電力線通訊(powerline communications, PLC) 最近研究採用多輸入多輸出(Multiple-input Multiple-output, MIMO) 的正交分頻多工(orthogonal frequencydivisionmultiplexing, OFDM) 系統，以改善過去在實體層(physical layer) 資料傳輸效能不足的問題，然而電力線系統除了存在可加性白高斯雜訊(Additive White Gaussian Noise, AWGN) 之外，還會產生具有高能量的脈衝雜訊(impulsive noise,IN)，導致系統的效能嚴重傷害。 有別於過去一些傳統的脈衝雜訊消除法，在本論文中我們使用一個名為壓縮感知(compressive sensing, CS) 的演算法來估計PLC 測脈衝雜訊的能量及其在傳送過程中發生的時機點後將其進行濾除的動作，為了證明CS 演算法的有效性，我們針對不同狀況下的脈衝雜訊做模擬分析，並搭配後續的通道估測及MIMO解調器，驗證系統的位元錯誤率(bit-error rate, BER) 在相同SNR 下能與無脈衝 雜訊時的性能相近。;Powerline communications(PLC) has been recently studied to apply the multipleinput multiple-output(MIMO)orthogonal frequency-division multiplexing (OFDM) technology in order to solve the problem of insufficient data transmission rate on the physical layer. However, the powerline system not only has the additive white Gaussian noise(AWGN), but also has high energy of impulsive noise(IN) that can do serious damage to the performance of the PLC system. Very different from some traditional impulsive noise elimination methods in the past, we develop an algorithm called compressive sensing(CS) in this thesis to estimate the energy of the impulsive noise and its presence position in the process of transmission and then filter it out. In order to show the effectiveness of the proposed algorithm, we simulate the MIMO PLC transmission with the impulsive noise in the different environments. Together with the MIMO channel estimation and different MIMO detection methods, we can see that the bit-error rate(BER) performance of the proposed algorithm can approach the case without the impulsive noise at the same SNR.
