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Blind Channel Estimation for MIMO Systems via Variational Inference by Tang, Jiancheng; Yang, Qianqian; Zhang, Zhaoyang is a scholarly article available to read on EtoBox.

What is Blind Channel Estimation for MIMO Systems via Variational Inference about?

In this paper, we investigate the blind channel estimation problem for MIMO systems under Rayleigh fading channel. Conventional MIMO communication techniques require transmitting a considerable amount of training symbols as pilots in each data block to obtain the channel state information (CSI) such that the transmitted signals can be successfully recovered. However, the pilot overhead and contamination become a bottleneck for the practical application of MIMO systems with the increase of the number of antennas. To overcome this obstacle, we propose a blind channel estimation framework, where we introduce an auxiliary posterior distribution of CSI and the transmitted signals given the received signals to derive a lower bound to the intractable likelihood function of the received signal. Meanwhile, we generate this auxiliary distribution by a neural network based variational inference framework, which is trained by maximizing the lower bound. The optimal auxiliary distribution which approaches real prior distribution is then leveraged to obtain the maximum a posterior (MAP) estimation of channel matrix and transmitted data. The simulation results demonstrate that the performance of

Author

Tang, Jiancheng; Yang, Qianqian; Zhang, Zhaoyang

Published

2021

Language

EN