@inproceedings{6e0412614ac74195a34705f3f7e25c57,
title = "A New K Best Sphere Decoder in 16 × 16 MIMO System using Deep Learning Algorithm",
abstract = "In this paper, a new K best sphere decoder is proposed for a 16× 16 MIMO receiver, in which the radius is determined by a deep learning mechanism using neural networks. The modified K best sphere decoders are having performances very close to maximum likelihood, with significantly reduced computational complexities as compared to that of the conventional detection techniques. The significant improvement in the achieved results is because of the deep learning algorithm's ability to limit the number of codewords at the receiver. The efficiencies of the resultant deep learning-based sphere decoder are evaluated in terms of spectral efficiency and symbol error rate. The effectiveness of the proposed algorithm is supported through the simulations carried on MATLAB software for 16× 16 MIMO systems, using 16 QAM modulation.",
keywords = "Deep learning (DL), K and Kl SD, Sphere decoder (SD), Symbol error rate (SER)",
author = "Priyanka Mishra and G. Singh",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 1st International Conference on Microwave, Antenna and Communication, MAC 2023 ; Conference date: 24-03-2023 Through 26-03-2023",
year = "2023",
doi = "10.1109/MAC58191.2023.10177100",
language = "English",
series = "International Conference on Microwave, Antenna and Communication, MAC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "International Conference on Microwave, Antenna and Communication, MAC 2023",
address = "United States",
}