The use of low-resolution data converters in the radio-frequency (RF) chains of all-digital massive multiple-input multiple-output (MIMO) basestations promises significant reductions in power consumption, hardware costs, and interconnect bandwidth. We propose a quantization-aware data-detection algorithm which mitigates the performance loss of 1-bit quantized massive MIMO orthogonal frequency-division multiplexing (OFDM) systems. Since the system performance heavily depends on the quality of channel estimates, we also develop a nonlinear 1-bit channel estimation algorithm that builds upon the proposed data detection algorithm. We show that the proposed algorithms significantly outperform linear data detectors and channel estimators in terms of bit error rate. For the proposed nonlinear data detection algorithm, we develop a very large scale integration (VLSI) architecture and present implementation results on a Xilinx Virtex-7 field programmable gate array (FPGA). Our implementation results are, to the best of our knowledge, the first for 1-bit massive MU-MIMO-OFDM systems and demonstrate comparable hardware efficiency with respect to state-of-the-art linear data detectors designed for systems with high-resolution data converters, while achieving lower bit error rate.

中文翻译：

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大规模MIMO-OFDM中1位数据检测的算法和VLSI设计

在全数字大规模多输入多输出（MIMO）基站的射频（RF）链中使用低分辨率数据转换器有望显着降低功耗，硬件成本和互连带宽。我们提出了一种量化感知数据检测算法，该算法可减轻1位量化大规模MIMO正交频分复用（OFDM）系统的性能损失。由于系统性能在很大程度上取决于信道估计的质量，因此我们还开发了一种非线性1位信道估计算法，该算法以提出的数据检测算法为基础。我们表明，在误码率方面，所提出的算法明显优于线性数据检测器和信道估计器。对于提出的非线性数据检测算法，我们开发了超大规模集成（VLSI）架构，并在Xilinx Virtex-7现场可编程门阵列（FPGA）上展示了实现结果。据我们所知，我们的实施结果是第一个1位大规模MU-MIMO-OFDM系统，并且展示了为高分辨率系统设计的最新线性数据检测器可比的硬件效率数据转换器，同时实现较低的误码率。