DocumentCode :
2209412
Title :
Nonlinear equalization with known channel state information in satellite communication
Author :
Li, Yinghua ; Deng, Yongjun
Author_Institution :
State Radio Monitoring Center, Beijing, China
fYear :
2008
fDate :
19-21 Nov. 2008
Firstpage :
1081
Lastpage :
1085
Abstract :
Three nonlinear equalization algorithms are discussed for the case that training sequence is not available but channel state information (CSI) is known. The first algorithm is based on the extended Kalman filter (EKF). The second one is based on decision feedback equalization (DFE), where a modified DFE (MDFE) is proposed. Both of the two algorithms use CSI directly. Independent of CSI, the third equalization algorithm is based on complex bilinear recurrent neural network (CBLRNN) and stop-and-go (S&G) algorithm. Simulation results show that MDFE is much better than the other two algorithms for nonlinear channels with either severe or mild intersymbol interference (ISI).
Keywords :
Kalman filters; channel estimation; decision making; intersymbol interference; recurrent neural nets; satellite communication; telecommunication computing; ISI; channel state information; complex bilinear recurrent neural network; decision feedback equalization; extended Kalman filter; intersymbol interference; nonlinear equalization algorithm; satellite communication; stop-and-go algorithm; AWGN; Artificial satellites; Channel state information; Decision feedback equalizers; Monitoring; Neural networks; Nonlinear distortion; Recurrent neural networks; Satellite communication; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Systems, 2008. ICCS 2008. 11th IEEE Singapore International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-2423-8
Electronic_ISBN :
978-1-4244-2424-5
Type :
conf
DOI :
10.1109/ICCS.2008.4737349
Filename :
4737349
Link To Document :
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