κ-μ阴影衰落信道下非数据辅助的误差矢量幅度性能分析
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摘要
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.
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.
引文
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[2]YACOUB M D.Theκ-μdistribution and theη-μdistribution[J].IEEE Antennas and Propagation Magazine,2007,49(1):68-81.
[3]HANZO L,NG S X,WEBB W T,et al.Quadrature amplitude modulation:from basics to adaptive trellis-coded,turbo-equalised and space-time coded OFDM,CDMA and MC-CDMA systems[M].IEEE Press-John Wiley,2004.
[4]SHAFIK R A,RAHMAN M S,ISLAM A H M R,et al.On the error vector magnitude as a performance metric and comparative analysis[C]//ICET'06.International Conference on Emerging Technologies,2006:27-31.
[5]周峰,张睿,高攸纲,等.五种失真因素综合作用下的EVM[J].电子学报,2012,40(3):607-610.ZHOU F,ZHANG R,GAO Y G,et al.Error vector magnitude by five distortion factors[J].Acta Electronica Sinica,2012,40(3):607-610.
[6]游长江,朱晓维,柳靖,等.基于射频前端的动态频谱共享无线通信系统工作信道选择分析[J].通信学报,2011,32(4):147-152.YOU C J,ZHU X W,LIU J.Analysis of operational channel selection of dynamic spectrum sharing wireless communication system based on RF front-end[J].Journal on Communications,2011,32(4):147-152.
[7]CHOUITEM R.EVM based AMC for an OFDM system[C]//Wireless Telecommunications Symposium(WTS),2010.IEEE,2010:1-5.
[8]LIU R,LI Y,CHEN H,et al.EVM estimation by analyzing transmitter imperfections mathematically and graphically[J].Analog Integrated Circuits and Signal Processing,2006,48(3):257-262.
[9]GEORGIADIS A.Gain,phase imbalance,and phase noise effects on error vector magnitude[J].IEEE Transactions on Vehicular Technology,2004,53(2):443-449.
[10]THOMAS V A,KUMAR S,KALYANI S,et al.Error vector magnitude analysis of fading SIMO channels relying on MRC reception[J].IEEE Transactions on Communications,2016,64(4):1786-1797.
[11]MAHMOUD H A,ARSLAN H.Error vector magnitude to SNR conversion for nondata-aided receivers[J].IEEE Transactions on Wireless Communications,2009,8(5):2694-2704.
[12]SEN S,SANTHAPURI N,CHOUDHURY R R,et al.Accu Rate:constellation based rate estimation in wireless networks[C]//NSDI.2010:175-190.
[13]PARIS J F.Statistical characterization ofκ-μshadowed fading[J].IEEE Transactions on Vehicular Technology,2014,63(2):518-526.
[14]ALAN J,DANIEL Z.Table of integrals,series and products(7th ed)[M].New York:Academic,2007.
[15]EXTON H.Multiple hypergeometric functions and applications[M].Halsted Press,Ellis Horwood,1976.
[16]3GPP TS 36.101.User Equipment(UE)radio transmission and reception[S].2010.
[17]SALTELLI A,CHAN K,SCOTT E M.Sensitivity analysis[M].New York:Wiley,2000.
[18]COTTON S L.Second-order statistics ofκ-μshadowed fading channels[J].IEEE Transactions on Vehicular Technology,2016,65(10):8715-8720.