Abstract
In the high mobility environment, the channel state information (CSI) in the last part of the packet is different from the beginning part’s actual channel. This phenomenon degrades channel estimation accuracy, and hence it is necessary to be compensated to realize reliable communications. Decision feedback channel estimation (DFCE) has been widely considered as the channel tracking approach. It still causes estimation errors due to the decision-making process in the presence of time and frequency selective fading environments. To address these issues, this paper newly proposes a generalized regression neural network (GRNN) based channel tracking scheme incorporated with frequency-domain CSI smoothing. The latter part is the key to improve the dependability of the training data sets. Computer simulation results confirm that the proposed scheme can achieve superior BER performance and the lower root mean square error (RMSE) value of estimated CSI better than the conventional ones.
Highlights
Packet-based transmission has been the most common wireless communication method, in which the desired transmission bitstream is divided into packets and transmitted
In order to overcome this problem, this paper newly proposes a frequency-domain channel state information (CSI) smoothing scheme for generalized regression neural network (GRNN) based channel tracking method
In this paper, we proposed the GRNN based channel tracking method that applied the smoothing preprocessing in order to refine incorrect desired responses produced by Decision feedback channel estimation (DFCE)
Summary
Packet-based transmission has been the most common wireless communication method, in which the desired transmission bitstream is divided into packets and transmitted. In this case, the propagation channel needs to be estimated for each packet in order to accurately equalize and decode the signal. The pilot-aided channel estimation (PCE) is one of the basic methods for channel estimation. There is a growing demand for reliable and high-capacity communications even in an environment where transmitters and receivers move at high speed. Under such a fast moving environment, the channel state rapidly changes
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