基于卡尔曼滤波的超宽带时变信道估计
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摘要
在超宽带时变信道估计中,针对状态转移系数估计不准确引起的滤波发散问题,提出一种基于状态转移系数门限修正的卡尔曼滤波信道估计方法。该方法对时变信道采用自回归模型(AR)进行建模,利用导频估计初始信道信息和信道状态转移系数,并对信道转移系数进行门限修正。仿真实验表明:和传统卡尔曼滤波算法相比,提出方法实现简单并能有效抑制滤波发散问题,提高时变信道估计精度。
In time-variant channel estimation for UWB system,for the filtering divergence problem caused by the inaccuracy of the state transfer coefficient,a Kalman filtering channel estimation method based on state transfer coefficient using threshold correction is proposed. The time-varying channel is modeled as an autoregressive(AR) process,then the initial channel information and channel state transfer coefficient are estimated by pilot,and the threshold of the channel state transfer coefficient is corrected. The simulation experiments show that compared with the traditional Kalman filtering algorithm,the proposed method is simple and can restrain filter divergence effectively and improve the accuracy of time-varying channel estimation.
In time-variant channel estimation for UWB system,for the filtering divergence problem caused by the inaccuracy of the state transfer coefficient,a Kalman filtering channel estimation method based on state transfer coefficient using threshold correction is proposed. The time-varying channel is modeled as an autoregressive(AR) process,then the initial channel information and channel state transfer coefficient are estimated by pilot,and the threshold of the channel state transfer coefficient is corrected. The simulation experiments show that compared with the traditional Kalman filtering algorithm,the proposed method is simple and can restrain filter divergence effectively and improve the accuracy of time-varying channel estimation.
引文
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[2]KEVIN W,PRATHABAN M,DANDEKAR K R.Measurement of the MIMO UWB OFDM channel[C]//2011 IEEERadio and Wireless Symposium,RWS 2011:21-24.
[3]HAJJAJ M,CHAINBI W,BOUALLEGUE R.Low-complexity WLMMSE channel estimator for MB-OFDM UWB systems[J].EURASIP Journal on Wireless Communications and Networking,2015,2015(1):56.
[4]RAJPUT A S,PRAJAPATI R.Performance of multiband UWB-OFDM in WPAN MIMO QAM communications system[J].International Journal of Electrical,Electronics and Computer Engineering,2015,4(2):121.
[5]WEN F,SING C C.Robust,low-complexity,and energy efficient downlink baseband receiver design for MB-OFDMUWB system[J].IEEE Transactions on Circuits and Systems I:Regular Papers,2012,59(2):399-408.
[6]ZHANG H,UDAGAWA T,ARITA T,et al.A statistical model for the small-scale multipath fading characteristics of ultra wideband indoor channel[C]//IEEE Conference on Ultra Wideband Systems and Technologies,2002:81-85.
[7]EMAMI S.UWB channel modeling[M].New York:Springer,2013:21-35.
[8]CHUDE-OKONKWO U A K,NGAH R,ZAHEDI Y K,et al.Measurement and parameter description of time-varying ultra-wideband infostation channel[J].Session 3P7 RF and Wireless Communication,2012:1476-1479.
[9]包志华,张士兵.OFDM-UWB系统在时变信道中的性能分析[J].南京邮电大学学报(自然科学版),2007,9(1):1-5.
[10]宋铁成,尤肖虎,沈连丰,等.基于导频和修正Kalman滤波的MIMO-OFDM信道估计方法[J].通信学报,2007,28(2):23-28.
[11]付梦印,邓志红,张继伟.Kalman滤波理论及其在导航系统中的应用[M].2版.北京:科学出版社,2010.
[12]MUNEER P,SAMEER S M.Doubly-selective channel estimation for OFDM systems using bernstein basis polynomials and Kalman-tracking[C]//Proceeding of 2012 Annual IEEEIndia Conference.India:IEEE Computer Society,2012:603-607.
[13]MADHESWARAN M.Performance analysis of multiband OFDM system over ultra wide band channels using Kalman filter[J].Wireless Personal Communications,2013,68(3):1121-1134.
[14]SNOW C,LAMPE L,SCHOBE R.Performance analysis of multiband OFDM for UWB communication[C]//Proceeding of ICC’05,Seoul,2005,4:2573-2578.
[15]JEMAI J,PIESIEWICZ R,GEISE I,et al.UWB Channel modeling within an aircraft cabin[C]//IEEE International Conference on Hannover,2008.
[16]LIN W T.The extended kalman filtering algo-rithm for carrier synchronization and the implemention[C]//IEEE ISCAS2006,4034-4037.