Affiliation:
1. Department of Electronic Engineering, Kyonggi University, Suwon 16227, Republic of Korea
Abstract
In this paper, we provide a light-weighted Machine Learning (ML) approach to channel estimation for New-Radio (NR) systems. Specifically, based on the equivalence between the Channel Impulse Response (CIR) in the time domain and its corresponding Channel Frequency Response (CFR) in the frequency domain, the light-weighted ML model for the channel estimation is shown to be established in comparison to the existing ML-based channel estimator. Furthermore, for practical use, the quantized weights for the light-weighted ML-based estimator are shown to be feasible without significant performance degradation in the sense of mean square error (MSE), which shows the effectiveness of the proposed approach from the perspective of memory overhead. Consequently, we show that there exists Signal to Noise Ratio (SNR) gain in comparison with the existing ML-based estimator, which is validated by numerical results considering the Sounding Reference Signal (SRS) for NR in the 3rd Generation Partnership Project (3GPP).
Funder
Institute of Information & Communications Technology Planning & Evaluation
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference27 articles.
1. Hou, X., Zhang, Z., and Kayama, H. (2009, January 20–23). DMRS Design and Channel Estimation for LTE-Advanced MIMO Uplink. Proceedings of the 2009 IEEE 70th Vehicular Technology Conference Fall, Anchorage, AK, USA.
2. Wang, Y., Zheng, A., Zhang, J., and Yang, D. (2009, January 16–18). A novel channel estimation algorithm for sounding reference signal in LTE uplink transmission. Proceedings of the 2009 IEEE International Conference on Communications Technology and Applications, Beijing, China.
3. Bertrand, P. (2011, January 15–18). Channel Gain Estimation from Sounding Reference Signal in LTE. Proceedings of the 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring), Budapest, Hungary.
4. Xia, X., Zhao, H., and Zhang, C. (2013, January 29–31). Improved SRS design and channel estimation for LTE-advanced uplink. Proceedings of the 2013 5th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, Chengdu, China.
5. Tran, H., Mai, T.-A., Dang, S., and Ngo, H.-A. (2018, January 29–31). Large-scale MU-MIMO uplink channel estimation using sounding reference signal. Proceedings of the 2018 2nd International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom), Ho Chi Minh City, Vietnam.