Abstract
In order to track 5G downlink shared channel in real time and meanwhile to reduce computational complexity, a linear minimum mean square error algorithm based on demodulation reference signal adaptive parameter estimation is proposed. Firstly, the SNR nonlinear centralized optimization problem is transformed into a multivariable linear programming problem due to the restriction of non-uniform energy distribution in time-domain channel. Secondly, considering the uncertainty of multipath delay channel, the combination of negative exponential distribution model and generalized correlation algorithm is taken advantage of so that the original problem is turned into a specific parameter optimization problem. At the same time, according to the obtained delay parameters and SNR, the most appropriate interpolation coefficient is selected for the LMMSE channel estimation by combining with the sliding window, which avoids the matrix inversion process, realizes the real-time matching of parameters, and reduces the computational complexity. The simulation results show that the proposed algorithm has better system performance compared with the classical channel estimation algorithm.
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This work is supported by National Key Research and Development Project (No. 2018YFB2100200).
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Deng, B., Min, X., Yu, S., Ye, Q. (2021). Channel Estimation Algorithm Based on Demodulation Reference Signal in 5G. In: Gao, H., Fan, P., Wun, J., Xiaoping, X., Yu, J., Wang, Y. (eds) Communications and Networking. ChinaCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 352. Springer, Cham. https://doi.org/10.1007/978-3-030-67720-6_25
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DOI: https://doi.org/10.1007/978-3-030-67720-6_25
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