Due to the power consumption and high circuit cost in antenna arrays, the practical application of multiple-input multiple-output (MIMO) in the unmanned aerial vehicle (UAV) communications and positioning is still challenging. Employing low-resolution analog-to-digital converters (ADCs) and hybrid analog and digital (HAD) structure is two low-cost choice 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 UAV positioning. By adopting the additive quantization noise model, the exact closed-form expression of the Cramer-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.

翻译：由于天线阵列的功耗和高电路成本，多输入多输出（MIMO）技术在无人机通信与定位中的实际应用仍面临挑战。采用低分辨率模数转换器（ADC）以及混合模拟与数字（HAD）结构是两种性能损失可接受的低成本方案。本文提出在接收端联合使用混合ADC架构与HAD结构以实现波达方向（DOA）估计，该技术将应用于无人机定位中的波束赋形跟踪与对准。通过引入加性量化噪声模型，推导出混合ADC的HAD架构下克拉美-罗下界（CRLB）的精确闭式表达式，同时导出性能损失因子的闭式表达式作为基准。此外，为考虑功耗问题，本文还研究了能效指标。数值结果表明，采用混合ADC的HAD结构能显著降低功耗与硬件成本，并且该架构可在性能损失与功耗之间实现更优折中。最终，在实际大规模MIMO系统中，采用2-4比特分辨率可能是较好的选择。