期刊文献+

瑞利信道下基于广义阈值函数的LDPC译码算法 被引量:1

LDPC Decoding Algorithm with Generalized Threshold-Function over Rayleigh Fading Channel
下载PDF
导出
摘要 现存的LDPC译码算法,其节点处理依据主要遵循大数逻辑准则和完全处理准则,对应的阈值参数一般是固定不变的,在性能和复杂度之间的均衡不够灵活.本文首先提出一种广义阈值函数,能应用于大多数基于可靠度的二元LDPC译码算法.通过调整阈值参数,可方便地控制参与迭代处理的节点队列.其次,本文提出一种基于伴随式和星座映射信息的非均匀量化译码算法,可进一步降低复杂度和存储负荷.实验结果显示,在瑞利信道下,本文算法能够在较低的量化比特下获得优良的译码性能;结合广义阈值函数,只有约30%的变量节点参与迭代运算,译码复杂度可显著降低. There exist two criterions for the existing LDPC decoding algorithms at node-processing,majority-logic processing and fully processing. The algorithms can't make flexible tradeoffs between performance and complexity,since their threshold parameters are usually set to be unvaried. This paper first presents a generalized threshold-function,which can apply to most of the existing binary LDPC decoding algorithms to control the participating-nodes in the iterations by adjusting the threshold parameters. Then a newnon-uniform quantization decoding algorithm combined with syndrome and constellation mapping information is presented,which can further reduce the complexity and memory load. Simulation results showthat the presented algorithm can obtain excellent decoding performances with very lowquantization level over the Rayleigh fading channel. Furthermore,it is shown that only 30% variable nodes are involved in the iterations when combined with the presented threshold-function,which can remarkably reduce the complexity.
出处 《电子学报》 EI CAS CSCD 北大核心 2017年第1期16-21,共6页 Acta Electronica Sinica
基金 国家自然科学基金(No.61102090 No.61261023 No.61362010) 广西自然科学基金(No.2012GXNSFAA053217 No.2014GXNSFBA118276)
关键词 LDPC码 阈值函数 迭代译码 译码复杂度 非均匀量化 LDPC code threshold-function iterative decoding decoding complexity non-uniform quantization
  • 相关文献

参考文献1

二级参考文献13

  • 1[10]Richardson T, Shodrollahi M A, Urbanke R. Design of Provably Good Low-Density Parity Check Codes. available at http://cm.bell-labs.com/cm/ms/former/tjr/pub.html
  • 2[11]Luby M, Mitzenmacher M, Shodrollahi M A, Spielman D A. Improved low density parity check codes using irregular graphs and belief propagation. In:Proc International Symposium on Information Theory(ISIT), Cambridge Massachusetts, USA, 1998. 117-129
  • 3[12]Davey M C, Mackay DJ. Low density parity check codes GF(q). IEEE Communications Letters, 1998, 2(6):165-167
  • 4[13]Hall E K, Wilson S G. Design and analysis of Turbo codes on Rayleigh fading channels. IEEE Journal on Selected Areas in Communications, 1998, 16(2):160-174
  • 5[1]Gallager R G. Low density parity check codes. IEE Trans Information Theory, 1962, 8(3): 208-220
  • 6[2]Berrou C, Blavieux A, Thitimajshima P. Near shammon limit error-correcting coding and decoding: Turbo-codes. In: Proc IEEE International Conference on Communications, Geneva, Switzerland, 1993. 1064-1070
  • 7[3]MacKay D J, Neal R M. Near shannon limit performance of low-density parity check codes. Electronic Letters, 1996,32(8): 1645-1646
  • 8[4]MacKay D J. Good error correcting codes based on very sparse matrices. IEEE Trans Information Theory, 1999, 45(2): 399-431
  • 9[5]Tanner R M. A recursive approach to low complexity codes. IEEE Trans Information Theory, 1981, 27(9): 533-547
  • 10[6]Richardson T, Urbanke R. The capacity of low-density parity-Check codes under message-passing decoding. IEEE Trans Information Theory, 2001,47(2): 478-496

共引文献12

同被引文献2

引证文献1

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部