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1. 重庆大学通信工程学院,重庆 400044
2. 重庆金美通信有限责任公司,重庆 400030
3. 中国移动通信集团重庆有限公司,重庆 400044
Online First:2018-05,
Published:25 May 2018
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Fan YANG, Xiaoping ZENG, Haiwei MAO, et al. Nondata-aided error vector magnitude performance analysis over κ−μ shadowed fading channel[J]. Journal on Communications, 2018, 39(5): 177-188.
Fan YANG, Xiaoping ZENG, Haiwei MAO, et al. Nondata-aided error vector magnitude performance analysis over κ−μ shadowed fading channel[J]. Journal on Communications, 2018, 39(5): 177-188. DOI: 10.11959/j.issn.1000-436x.2018088.
κ−μ阴影衰落信道下系统性能预测是无线通信中一个具有挑战性的问题,严重影响着传输机制设计。针对此问题,提出一种采用非数据辅助的误差矢量幅度(NDA-EVM
nondata-aided error vector magnitude)对κ−μ阴影衰落信道进行性能分析的理论方法。选取NDA-EVM作为反映信道变化的评估参量,采用最大似然准则推导阴影衰落信道下不同调制阶数NDA-EVM统一的计算模型,并以衰落因子为中间变量,建立NDA-EVM与κ−μ分布的联系,据此推导NDA-EVM 在κ−μ阴影衰落信道的理论下限,并化简给出几种典型信道的性能界限。对所得结论进行理论分析和数值仿真模拟,结果表明:相较传统的DA-SNR(data-aided signal to noise ratio)和DA-EVM(data- aided error vector magnitude),NDA-EVM对κ−μ阴影衰落信道的评估具有最小均方根误差;推导的下限与理论值有很高的吻合度,特别是在低SNR时为紧下界;下限与κ−μ阴影衰落信道参数均呈负相关特性,对信道变化非常敏感。
The performance prediction of wireless system over κ−μ shadowed fading channels was a challenging problem of wireless communications
which affects transmission scheme design seriously.To solve this problem
a novel method of quantifying the κ−μ shadowed fading channels performance based on nondata-aided error vector magnitude (NDA-EVM) was proposed.NDA-EVM was considered as a new metric to evaluate the change of the channels.The unified model to calculate different modulation order of NDA-EVM was analytically derived by maximum likelihood criterion.Moreover
the relationship between the κ−μ distribution and the NDA-EVM was built by using the attenuation factor of the channel as intermediate variable.Thereafter
the lower bounds of the NDA-EVM over the κ−μ shadowed fading channels were formulated
which was also simplified for various typical channels.The theoretical analysis was taken
moreover
numerical results were also conducted to verify the effectiveness of the derived formulation.It shows that NDA-EVM estimation has the lest root mean square error than data-aided signal to noise ratio (DA-SNR) estimation and error vector magnitude (DA-EVM) estimation over the κ−μ shadowed fading channels.The derived lower bounds closely match the theoretical values
especially at low SNR.In addition
the lower bounds are negatively related to all of the parameters of the κ−μ shadowed fading channels
which make it sensitive to the change of the fading channels.
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