2008年在國際資訊理論ISIT會議上，土耳其畢爾肯大學教授Arikan首次提出了通道極化的概念，基於該理論，他給出了已知的第一種能夠被嚴格證明達到通道容量的通道編碼方法，並命名為極化碼（Polar code）。極化碼具有明確而簡單的編碼及解碼演算法，而在2016年，極化碼成為5GeMBB情況的控制通道編碼方案。對於有線通訊或無線通訊，脈衝雜訊是很嚴重的問題，瞬間的強力干擾不僅會破壞傳送的訊號，還會使系統在資料的解讀上產生大量的錯誤。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。本篇論文將利用巴氏參數對極化通道進行2種可靠度估測方式來編制凍結位元(frozen bits)以及利用系統性編碼(systematic encoding)、系統性接續消去解碼(systematic Successive Cancellation decoding)和系統性信仰傳送解碼(systematic Belief Propogation decoding)並加入剪裁器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。

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 , and named it Polar Code. Based on this concept, polar codes, the first channel coding method that can be rigorously proved to achieve the capacity of the channel appeared. Polar code has a clear and simple encoding and decoding algorithm. 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 2 different polarization channels reliability estimation methods under Bhattacharyya Parameter to create frozen bits under memoryless noise channels, add clipper, and the performance of the polar codes generated by systematic encoding, systematic Successive Cancellation decoding and systematic Belief Propogation decoding.

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