Title :
Nonlinear equalization with known channel state information in satellite communication
Author :
Li, Yinghua ; Deng, Yongjun
Author_Institution :
State Radio Monitoring Center, Beijing, China
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;
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
DOI :
10.1109/ICCS.2008.4737349