Multicast beamforming planning based on massive MIMO antenna array

Xiaoxiao Liu; Haoran Mei; Limei Peng

doi:10.1117/12.2607219

28 October 2021 Multicast beamforming planning based on massive MIMO antenna array

Xiaoxiao Liu, Haoran Mei, Limei Peng

Proceedings Volume 11884, International Symposium on Artificial Intelligence and Robotics 2021; 118841Z (2021) https://doi.org/10.1117/12.2607219
Event: International Symposium on Artificial Intelligence and Robotics 2021, 2021, Fukuoka, Japan

Abstract

Massive MIMO and beamforming are primary technologies in 5G and beyond (B5G). The line-of-sight (LOS) beamforming technology form a beam path for a specific user to significantly compensates for the high attenuation of millimeter-wave (mmWave). This paper considers serving multicast users using beamforming based on the massive MIMO antenna array, aiming to optimize the beam utilization and maximize the successfully served users. In particular, we divide the massive MIMO antenna array into multiple smaller sub-arrays with different scales to form flexible beams with various beam widths and transmission coverage to serve unicast or multicast users based on needs. Regarding this, we propose an Integer Linear Programming (ILP) optimization model to minimize the power consumption of the entire antenna array while maximizing the number of successfully served users using beamforming multicast and/or unicast, subject to the constraints of power consumption and signal-to-interference-noise ratio (SINR). The proposed optimization model is numerically evaluated, and results show that significant power can be saved using multicast beamforming technology

Citation Download Citation

Xiaoxiao Liu, Haoran Mei, and Limei Peng "Multicast beamforming planning based on massive MIMO antenna array", Proc. SPIE 11884, International Symposium on Artificial Intelligence and Robotics 2021, 118841Z (28 October 2021); https://doi.org/10.1117/12.2607219

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KEYWORDS

Antennas

Optimization (mathematics)

Computer programming

Signal attenuation

Signal to noise ratio

Signal processing

Power supplies

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