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Development of Chinese State Funds in Front of a Global Economic, Monetary and Financial Strategy

Autor

  • Sébastien Chevais

DOI:

https://doi.org/10.21641/demo.773

Słowa kluczowe:

channel estimation

Abstrakt

This paper studies estimating the channel state information at the end of receiver (CSIR) for multiple transmitters communicating with only one receiver so that the latter can decode the incoming signal more efficiently. The transmitters and the receiver are all equipped with multi-antennas and using orthogonal space-time block codes (OSTBC). An algorithm is developed based on deep learning for estimating multi-user multiple-input multiple-output (MU-MIMO) channels. The algorithm could estimate the CSIR using a single pilot block. The proposed convolutional neural network (CNN) architecture designed for this task begins with an input layer that accepts grayscale images, followed by six convolutional blocks for feature extraction and processing. The network concludes with a fully connected layer to output the estimated channel information. It is trained using a regression loss function to map input images to accurate channel information accurately. The performance of the proposed method is compared with classical methods like least square and subspace-based methods, including Capon and rank revealing QR (RRQR) methods. CNN achieved better performance in comparison with the reference. Computer simulations are included to validate the proposed method.

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Bibliografia

J. Kaur et al., "Machine Learning Techniques for 5G and Beyond", IEEE Access, vol. 9, pp. 23472-23488, 2021.

C. Xu et al., "Two Decades of MIMO Design Tradeoffs and Reduced-complexity MIMO Detection in Near-capacity Systems", IEEE Access, vol. 5, pp. 18564-18632, 2017.

Z. An et al., "Blind High-order Modulation Recognition for Beyond 5G OSTBC-OFDM Systems via Projected Constellation Vector Learning Network", IEEE Communications Letters, vol. 26, no. 1, pp. 84-88, 2022.

R. Chataut and R. Akl, "Massive MIMO Systems for 5G and Beyond Networks - Overview, Recent Trends, Challenges, and Future Research Direction", Sensors, vol. 20, no. 10, art. no. 2753, 2020.

C.M. Lau, "Performance of MIMO Systems Using Space Time Block Codes (STBC)", Open Journal of Applied Sciences, vol. 11, pp. 273-286, 2021.

Opublikowane

30-12-2022

Jak cytować

Chevais, Sébastien. „ Development of Chinese State Funds in Front of a Global Economic, Monetary and Financial Strategy ”. DEMO, grudzień 2022, s. 226-51, doi:10.21641/demo.773.

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