資訊的可靠度在通訊系統和儲存裝置一直以來都是相當重要的，為了要讓可靠度提升，最常使用的方法是錯誤控制碼，而錯誤控制碼又分為錯誤偵測碼和錯誤更正碼兩種。低密度奇偶檢查碼是錯誤更正碼的一種，由於低密度奇偶檢查碼能達到極佳的效能，因此現在廣為被大家使用。
類循環低密度奇偶檢查碼是低密度檢查碼的子分類，由於具有相當佳的結構性，在編碼器的實現上相較於一般的低密度奇偶檢查碼來說更為容易，因此本文使用類循環低密度奇偶檢查碼作為編碼的碼使用。在創建同位檢查矩陣時，則是採用拉丁方陣的方式去創建的。
由於類循環低密度奇偶檢查碼的生成矩陣相當具有結構性，在計算碼字的同位檢查位元時，硬體可以重複使用，若是輸入訊息進入編碼器時以序向方式一個位元一個位元輸入，會耗費許多時間，若是一次輸入多一點位元進入編碼器去計算的話，則可以省下不少時間，因此本篇文章是採用平行輸入的方式將訊息送進編碼器，以節省計算時間。所設計的編碼器進行合成時所合出來的閘數為53K。

Reliability of information is always quite important for communication systems and storages. The most often used strategy to increase reliability is Error Control Code. Error Control Code can be classified into two kinds: Error Detecting Code and Error Correcting Code. LDPC code is one of Error Correcting Code. Because LDPC code can achieve great performance, it is widely used now.
Quasi-cyclic LDPC code is a subclass of LDPC code. Due to its great structure, the implement of a quasi-cyclic low-density parity-check code encoder is quite easier compared with that of LDPC code, so we choose quasi-cyclic LDPC code as our code to use. As to parity-check matrix, we use Latin square to construct it.
Because the structure of the encoder is not complex, hardware can be reused when calculating parity check bits. If we input our information into the encoder one bit by one bit, it will take so much time. So, if we input more bits into the encoder one time, it will save much time. To save time, I use parallel methods to input information bits. The gate count of my designed encoder is 53k.

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[2] Yunghsiang S. Han, from the class note, ”http://ct.ee.ntust.edu.tw/ldpc.pdf ”

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[6] Li Zhang, Qin Huang, Shu Lin, Abdel-Ghaffar, K., and Blake, I.F.,” Quasi-Cyclic
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[7] Jyun-Ren Yu, ”Decoder Implementation of Latin Squares LDPC Codes, ” Master
Thesis, National Taiwan University of Science and Technology, Taipei,
Taiwan(2013)