咨询与建议

看过本文的还看了

相关文献

该作者的其他文献

文献详情 >Application of turbo TCM codes... 收藏

Application of turbo TCM codes for impulsive noise channel

作     者:Koike, K Ogiwara, H 

作者机构:Nagaoka Univ Technol Fac Engn Nagaoka Niigata 9402188 Japan 

出 版 物:《IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES》 (电子信息通信学会汇刊:电子学、通信及计算机科学基础)

年 卷 期:1998年第E81A卷第10期

页      面:2032-2039页

核心收录:

学科分类:0808[工学-电气工程] 0809[工学-电子科学与技术(可授工学、理学学位)] 08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

主  题:turbo codes trellis coding coded modulation impulsive noise 

摘      要:A turbo TCM system is applied to a channel with overall noise which is equal to the additive combination of impulsive Gaussian noise and Additive White Gaussian Noise (AWGN). By taking the distribution of the previously mentioned overall noise into account, a decoding algorithm for Poisson occurrence impulsive noise is derived as an extension of that for AWGN. A simulation result shows that E-b/N-0 difference from Shannon limit to realize BER=10(-4) is 0.493 dB. To investigate the effect of burst noise, we discuss the case of additive impulsive noise with Markovian occurrence which is represented by Hidden Markov Model. A decoding algorithm for Markovian noise is proposed. In the iterative decoding for the Markovian channel, the decoding algorithms for Markovian and Poisson noise are applied separately to the two component decoders. The decoding algorithm for Markovian noise is used in the component decoder wherein received signal is directly fed, while the decoding algorithm for Poisson noise is used in the component decoder wherein received signal is fed after passing an interleaver. This paper also shows simulation results that include the effects of varying the noise parameters in the decoding. In the Markovian case, when smaller value of variance of impulsive noise is used, the observed flattening of BER performance is more serious compared to the effect in the Poisson noise channel. No flattening is observed when large value is used.

读者评论 与其他读者分享你的观点

用户名:未登录
我的评分