Deep Learning Based Channel Estimation in Data Driven MIMO Receiver
Keywords:
OFDM, MIMO, Space Time Trellis Code, Frequency Index Modulation, Compressed Sensing (CS), Channel EstimationAbstract
OFDM (orthogonal frequency division multiplexing) is a wireless network methodology that sends multiple data streams across a particular channel while effectiently handling inter-symbol interference and enhancing frequency band available. And since the antenna is sending signals, evaluating the noise in a noisy channel is essential. This research aims into compressed sensing (CS) as a way to improve throughput and BER performance by transmitting additional data bits within every subcarrier frame whilst still limiting detector unpredictability. The Neuro-LS methodology is used in this study to generate a soft trellis decoding algorithm through channel estimation. Trellis decoding performs better BER, and DNN relying channel estimation outperforms BER, according to the findings.
Metrics
References
Le, Ha An et al. “Machine Learning-Based 5G-and-Beyond Channel Estimation for MIMO-OFDM Communication Systems.” Sensors (Basel, Switzerland) vol. 21,14 4861. 16 Jul. 2021, doi:10.3390/s21144861
Raviteja, P., Phan, K. T., Hong, Y., & Viterbo, E. (2018). Interference cancellation and iterative detection for orthogonal time frequency space modulation. IEEE Transactions on Wireless Communications, 17(10), 6501–6515. https://doi.org/10.1109/TWC.2018.2860011
Basar, E., Wen, M., Mesleh, R., Di Renzo, M., Xiao, Y., & Haas, H. (2017). Index Modulation Techniques for Next-Generation Wireless Networks. IEEE Access, 5, 16693–16746. https://doi.org/10.1109/ACCESS.2017.2737528
Mao, T., Wang, Q., Wang, Z., & Chen, S. (2019). Novel index modulation techniques: A survey. In IEEE Communications Surveys and Tutorials (Vol. 21, Issue 1). IEEE. https://doi.org/10.1109/COMST.2018.2858567
Cheng, X., Zhang, M., Wen, M., & Yang, L. (2018). Index modulation for 5G: Striving to do more with less. IEEE Wireless Communications, 25(2), 126–132. https://doi.org/10.1109/MWC.2018.1600355
Prabaharan, N., & Palanisamy, K. (2017). A comprehensive review on reduced switch multilevel inverter topologies, modulation techniques and applications. Renewable and Sustainable Energy Reviews, 76(January 2016), 1248–1282. https://doi.org/10.1016/j.rser.2017.03.121
Universitatea Tehnica? “Gh. Asachi” Ias?i. Faculty of Electronics, T. and I. T., IEEE Romania Section. CAS Chapter, IEEE Circuits and Systems Society, & Institute of Electrical and Electronics Engineers. (2017). ISSCS 2017 : International Symposium on Signals, Circuits and Systems : 13 - 14 July, 2017, lasi, Romania.
Wen, M., Zheng, B., Kim, K. J., Di Renzo, M., Tsiftsis, T. A., Chen, K. C., & Al-Dhahir, N. (2019). A Survey on Spatial Modulation in Emerging Wireless Systems: Research Progresses and Applications. IEEE Journal on Selected Areas in Communications, 37(9), 1949–1972. https://doi.org/10.1109/JSAC.2019.2929453
Cai, Y., Qin, Z., Cui, F., Li, G. Y., & McCann, J. A. (2018). Modulation and Multiple Access for 5G Networks. IEEE Communications Surveys and Tutorials, 20(1), 629–646. https://doi.org/10.1109/COMST.2017.2766698
Siwakoti, Y. P., & Blaabjerg, F. (2018). Common-ground-type transformerless inverters for single-phase solar photovoltaic systems. IEEE Transactions on Industrial Electronics, 65(3), 2100–2111. https://doi.org/10.1109/TIE.2017.2740821
Ye, H., Li, G. Y., & Juang, B. H. (2018). Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems. IEEE Wireless Communications Letters, 7(1), 114–117. https://doi.org/10.1109/LWC.2017.2757490
Zheng, B., & Zhang, R. (2020). Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization. IEEE Wireless Communications Letters, 9(4), 518–522. https://doi.org/10.1109/LWC.2019.2961357
Jaradat, A. M., Hamamreh, J. M., & Arslan, H. (2020). OFDM with hybrid number and index modulation. IEEE Access, 8, 55042–55053. https://doi.org/10.1109/ACCESS.2020.2982088
Yang, Z., Wu, B., Zheng, K., Wang, X., & Lei, L. (2016). A survey of collaborative filtering-based recommender systems for mobile internet applications. IEEE Access, 4, 3273–3287. https://doi.org/10.1109/ACCESS.2016.2573314
Jaradat, A. M., Hamamreh, J. M., & Arslan, H. (2019). Modulation Options for OFDM-Based Waveforms: Classification, Comparison, and Future Directions. IEEE Access, 7(1), 17263–17278. https://doi.org/10.1109/ACCESS.2019.2895958
Felix, A., Cammerer, S., Dorner, S., Hoydis, J., & Ten Brink, S. (2018). OFDM-Autoencoder for End-to-End Learning of Communications Systems. IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, 2018-June. https://doi.org/10.1109/SPAWC.2018.8445920
Wen, M., Li, Q., Basar, E., & Zhang, W. (2018). Generalized multiple-mode OFDM with index modulation. IEEE Transactions on Wireless Communications, 17(10), 6531–6543. https://doi.org/10.1109/TWC.2018.2860954
Jawhar, Y. A., Audah, L., Taher, M. A., Ramli, K. N., Shah, N. S. M., Musa, M., & Ahmed, M. S. (2019). A Review of Partial Transmit Sequence for PAPR Reduction in the OFDM Systems. IEEE Access, 7(1), 18021–18041. https://doi.org/10.1109/ACCESS.2019.2894527
Baquero Barneto, C., Riihonen, T., Turunen, M., Anttila, L., Fleischer, M., Stadius, K., Ryynänen, J., & Valkama, M. (2019). Full-Duplex OFDM Radar with LTE and 5G NR Waveforms: Challenges, Solutions, and Measurements. IEEE Transactions on Microwave Theory and Techniques, 67(10), 4042–4054. https://doi.org/10.1109/TMTT.2019.2930510
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Vimlesh Gour, Mr. Kamal Niwaria, Dr. Bharti Chourasia

This work is licensed under a Creative Commons Attribution 4.0 International License.