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解放军信息工程大学信息系统工程学院,河南 郑州 450002
[ "黄强(1993-),男,江西上饶人,解放军信息工程大学硕士生,主要研究方向为盲信号处理等。" ]
[ "彭华(1973-),男,江西萍乡人,解放军信息工程大学教授、博士生导师,主要研究方向为软件无线电、通信信号处理等。" ]
[ "李天昀(1979-),男,江西萍乡人,博士,解放军信息工程大学副教授,主要研究方向为通信信号处理等。" ]
[ "巩克现(1975-),男,山东泰安人,博士,解放军信息工程大学副教授,主要研究方向为信道编译码技术、通信信号处理等。" ]
网络出版日期:2017-04,
纸质出版日期:2017-04-25
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黄强, 彭华, 李天昀, 等. 基于软信息联合修正的非对称PCMA盲分离算法[J]. 通信学报, 2017,38(4):178-189.
Qiang HUANG, Hua PENG, Tian-yun LI, et al. Blind separation of asymmetric PCMA signal based on soft information joint correction[J]. Journal on communications, 2017, 38(4): 178-189.
黄强, 彭华, 李天昀, 等. 基于软信息联合修正的非对称PCMA盲分离算法[J]. 通信学报, 2017,38(4):178-189. DOI: 10.11959/j.issn.1000-436x.2017044.
Qiang HUANG, Hua PENG, Tian-yun LI, et al. Blind separation of asymmetric PCMA signal based on soft information joint correction[J]. Journal on communications, 2017, 38(4): 178-189. DOI: 10.11959/j.issn.1000-436x.2017044.
针对非对称PCMA信号盲分离问题,在一种低复杂度的盲分离结构基础上,提出基于软信息联合修正提高强弱信号解调性能的盲分离算法。该算法利用强弱信号解调相互的影响,通过尝试修正高出错概率的强信号接收符号,比较修正前后强弱信号符号星座质量(软信息)的优劣来决定是否修正当前强弱信号的硬判决值,从而降低强弱信号解调误码率。仿真结果表明,当强信号信噪比高于17 dB时,强弱信号解调误码率分别降低近2个数量级,且算法计算复杂度低于传统基于重构抵消算法的计算复杂度。
On the basis of a blind separation structure with low complexity
an efficient blind separation algorithm based on soft information joint correction was proposed for asymmetric PCMA to improve the demodulation performance of strong and weak signals.By utilizing the demodulation mutual influence between the strong and weak signals
this algorithm tried to correct the receiving symbols of strong signal with high error probability.Comparing the symbol constellation quality (soft information) of signals before and after correction
it can be decided whether the hard decision values of strong and weak signals need to be modified
which efficiently reduce the demodulation error rate of strong and weak signals.The simulation results show that
the demodulation error rate of strong and weak signals can be reduced by nearly two orders of magnitude after joint correction especially when the signal to noise ratio of strong signal is higher than 17 dB
and the computational complexity of this algorithm is lower than that of the conventional reconstruction cancellation algorithm.
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