Autors: Mihaylova, D. A., Valkova-Jarvis, Z. V., Poulkov, V. K., Stoynov, V. R., Iliev, G. L.
Title: Investigation of Hybrid Beamforming in mmWave Massive MIMO Systems
Keywords: hybrid beamforming, millimeter waves, massive MIMO

Abstract: Conventional MIMO systems usually achieve diversity gain by the use of baseband Digital Signal Processing. However, in millimeter wave massive MIMO systems digital precoding is impractical, due to the large antenna array which increases the energy consumption and processing complexity. To alleviate these problems, hybrid beamforming can be used instead. In this paper, the main principles and major considerations of hybrid beamforming are presented. A low-complexity hybrid precoder is discussed and its performance is investigated in scenarios where large numbers of users are served.

References

    Issue

    IEEE IDAACS-SWS 2020 - The 5th IEEE International Symposium on Smart and Wireless Systems within the International Conferences on Intelligent Data Acquisition and Advanced Computing Systems, 17-18 September, 2020, Dortmund, Germany, 2020, Germany, ISBN: 978-17281-9960-3; DOI: 10.1109/IDAACS-SWS50031.2020.9297057

    Цитирания (Citation/s):
    1. S. Lavdas, P.K. Gkonis, E. Tsaknaki, L. Sarakis, P. Trakadas, K. Papadopoulos, “A Deep Learning Framework for Adaptive Beamforming in Massive MIMO Millimeter Wave 5G Multicellular Networks”, Electronics (Switzerland), vol. 12, no. 17, art. no. 3555, September 2023. DOI: 10.3390/electronics12173555 - 2023 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus