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Post and pre-layout analysis of Low Density Parity Check (LDPC) decoder using 120nm technology Cadence Encounter Tool

机译:低密度奇偶校验(LDPC)解码器使用120nm技术Cadence遇到工具的发布和预布局分析

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Low Density Parity Check (LDPC) codes are the one most powerful error correction codes (ECCs) and approach the Shannon limit[1]. The main advantage of the parity check matrix is the decoder can correct all single-bit errors. A decoding algorithm called Min-Sum (MS) algorithm is used in LDPC decoder. In a MIN-SUM decoding algorithm, check node units (CNU) and variable node units (VNU) are iteratively exchange messages with one another following the rule described by the Tanner graph. Min-Sum decoding is widely used for decoding LDPC codes in many modern digital video broadcasting decoding due to its relative low complexity and robustness against quantization error. In this proposed method, the front-end design flow is done in Verilog and the hardware core is simulated in ModelSim and the performance analysis for various parameters are area (2.153mm2), power(59.035mW)and memory (260.864Megabytes). The Design Rule Check (DRC) is done for back-end design flow by using Cadence Encounter Tool and the comparison results are analysed between the pre-layout and post-layout design flow of LDPC Decoder.
机译:低密度奇偶校验(LDPC)码是一个最强大的纠错码(ECC),并接近香农极限[1]。奇偶校验矩阵的主要优势是解码器可以纠正所有的单比特错误。称为最小和译码算法(MS)算法在LDPC解码器中使用。在一个MIN-sum解码算法,校验节点单元(CNU)和变量节点单元(VNU)是彼此迭代地交换的消息遵循由Tanner图中描述的规则。 Min-Sum译码被广泛用于许多现代数字视频广播解码解码LDPC码,由于其相对较低的复杂性和稳健性对量化误差。在该提出的方法中,前端设计流程以Verilog完成,硬件核心中模拟的ModelSim和各种参数的性能分析是区域(2.153平方毫米),功率(59.035mW)和存储器(260.864Megabytes)。设计规则检查(DRC)是通过使用Cadence遭遇工具后端设计流程进行,比较结果被LDPC解码器的预布局和后布局设计流程之间进行分析。

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