Low-Complexity Detection and Decoding Scheme for LDPC-Coded MLC NAND Flash Memory

来源 :中国通信(英文版) | 被引量 : 0次 | 上传用户:zbwang12315
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
With the development of manufac-ture technology, the multi-level cell (MLC) technique dramatically increases the storage density of NAND flash memory. As the result, cell-to-cell interference (CCI) becomes more serious and hence causes an increase in the raw bit error rate of data stored in the cells. Recently, low-density parity-check (LDPC) codes have appeared to be a promising solu-tion to combat the interference of MLC NAND flash memory. However, the decoding complexity of the sum-product algorithm (SPA) is extremely high. In this paper, to im-prove the accuracy of the log likelihood ratio (LLR) information of each bit in each NAND flash memory cell, we adopt a non-uniform detection (N-UD) which uses the average maximum mutual information to determine the value of the soft-decision reference voltag-es. Furthermore, with an aim to reduce the de-coding complexity and improve the decoding performance, we propose a modified soft reli-ability-based iterative majority-logic decoding (MSRBI-MLGD) algorithm, which uses a non-uniform quantizer based on power func-tion to decode LDPC codes. Simulation results show that our design can offer a desirable trade-off between the performance and com-plexity for high-column-weight LDPC-coded MLC NAND flash memory.
其他文献
压疮如不及时治疗及护理,坏死可发展到深层组织,侵害肌肉、肌腱和骨骼,造成严重感染,危及生命.
The spectral analysis method is suitable for the process control and the process analysis such as the fast evaluation of crude oils. In this study, model transf
期刊
压疮的防治一直是困扰临床医务人员的难题.2004年8月-2006年8月,本研究对我院老年科收治的318例卧床患者选用Waterlow压疮危险因素评估表及其分级预防护理法进行压疮的预测及
目的了解畹町经济开发区鼠疫疫源地的活动现状,为预防控制鼠疫提供科学数据。方法采用常规鼠疫监测方法,监测鼠疫宿主、媒介数量的变化趋势,并进行统计分析。结果 2004-2013
股骨颈骨折多发于老年人,行下肢骨牵引是治疗方法之一.由于长期牵引使局部受压、疼痛、抬臀及更换床单困难、潮湿刺激皮肤等因素,致使患者臀部、骶尾部容易发生压力性溃疡.
5岁以下儿童死亡监测是妇幼卫生工作的重要内容之一,是评价儿童健康的重要指标,也是政府部门进行妇幼卫生工作计划、管理和决策的重要依据。为了解颍东区5岁以下儿童死亡病例
目的基于3维骨架的行为识别研究在计算机视觉领域一直是非常活跃的主题,在监控、视频游戏、机器人、人机交互、医疗保健等领域已取得了非常多的成果。现今的行为识别算法大多选择固定关节点作为坐标中心,导致动作识别率较低,为解决动作行为识别中识别精度低的问题,提出一种自适应骨骼中心的人体行为识别的算法。方法该算法首先从骨骼数据集中获取三维骨架序列,并对其进行预处理,得到动作的原始坐标矩阵;再根据原始坐标矩阵提
On August 22,at the Summit Forum on Green,Digitalized,High-quality and Innovative Development of Rubber Industry held in Yinchuan,Ningxia,China Rubber periodica
期刊