Document Type

Journal Article

Publication Title

IEEE Open Journal of the Communications Society

Publisher

IEEE

School

School of Science / Security Research Institute

RAS ID

61897

Funders

National Natural Science Foundation of China / Hainan Province Science and Technology Special Fund / Scientific Research Fund Project of Hainan University

Comments

Shi, B., Zhang, Q., Dong, R., Jie, Q., Yan, S., Shu, F., & Wang, J. (2023). DOA estimation for hybrid massive MIMO systems using Mixed-ADCs: Performance loss and energy efficiency. IEEE Open Journal of the Communications Society, 4, 1383-1395. https://doi.org/10.1109/OJCOMS.2023.3290075

Abstract

Due to the power consumption and high circuit cost in antenna arrays, the practical application of massive multiple-input multiple-output (MIMO) in the sixth generation (6G) and future wireless networks is still challenging. Employing low-resolution analog-to-digital converters (ADCs) and hybrid analog and digital (HAD) structure is two low-cost choices with acceptable performance loss. In this paper, the combination of the mixed-ADC architecture and HAD structure employed at receiver is proposed for direction of arrival (DOA) estimation, which will be applied to the beamforming tracking and alignment in 6G. By adopting the additive quantization noise model, the exact closed-form expression of the Cramér-Rao lower bound (CRLB) for the HAD architecture with mixed-ADCs is derived. Moreover, the closed-form expression of the performance loss factor is derived as a benchmark. In addition, to take power consumption into account, energy efficiency is also investigated in our paper. The numerical results reveal that the HAD structure with mixed-ADCs can significantly reduce the power consumption and hardware cost. Furthermore, that architecture is able to achieve a better trade-off between the performance loss and the power consumption. Finally, adopting 2-4 bits of resolution may be a good choice in practical massive MIMO systems.

DOI

10.1109/OJCOMS.2023.3290075

Creative Commons License

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

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