極化碼(Polar Code)是一個新興的編碼方式。2008年在國際資訊理論ISIT會議上，土耳其畢爾肯大學Arikan教授首次提出了通道極化的概念，基於此概念，第一種能夠被嚴格證明達到通道容量的通道編碼方法——極化碼就此出現，而在2016年，極化碼成為5G eMBB場景的控制頻道編碼方案。
對於有線通訊或無線通訊，脈衝雜訊是最令人頭痛的問題，其原因為脈衝雜訊不同於一般的可加性高斯白雜訊(AWGN)，其能量往往是可加性高斯白雜訊的數十倍甚至數百倍。常見的脈衝雜訊模型可分為有記憶型態的Markov-Gaussian通道模型以及無記憶型態的Bernoulli-Gaussian和Additive White Class A Noise通道模型。本篇論文將探討利用不同的極化通道可靠性估測方式，編制凍結位元(frozen bits)以及系統編碼(systematic encoding)與非系統編碼(nonsystematic encoding)所造出的極化碼在無記憶型態的脈衝雜訊模型中的性能表現。

Polar code is an emerging channel coding. In 2008, at the meeting of International Information Theory ISIT, Professor Erdal Arikan of Bilkent University in Turkey first proposed the concept of channel polarization. Based on this concept, polar codes, the first channel coding method that can be rigorously proved to achieve the capacity of the channel appeared. In 2016, the polar code became the control channel coding scheme for the 5G eMBB scene.
Impulse noise becomes one of the problems in the wired and wireless communication systems. As the impulse noise is different from the general AWGN noise, the energy of impulse noise is often hundreds of times that of the AWGN noise. Common impulse noise models can be divided into memory noise channels, Markov-Gaussian channel models, and memoryless noise channels, Bernoulli-Gaussian and Additive White Class A Noise channel. This paper will explore the performance of using different polarization channels reliability estimation methods to create frozen bits under memoryless noise channels, and the performance of the polar codes generated by systematic encoding and nonsystematic encoding.

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