High Order QAM Modulation in Massive MIMO Systems with Asymmetrically Quantized 1-bit ADCs

Deploying 1-bit analog-to-digital converters (ADCs) in massive multiple-input multiple-output (MIMO) systems is promising to reduce the energy consumption. However, serious quantization errors limit the feasibility of high order quadrature amplitude modulation (QAM). This paper focuses on the perfor...

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Veröffentlicht in:IEEE transactions on wireless communications 2023-09, Vol.22 (9), p.1-1
Hauptverfasser: Sun, Bule, Tang, Xiaogang, Zhou, Yiqing, Pan, Zhengang, Lin, Hai
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Sprache:eng
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Zusammenfassung:Deploying 1-bit analog-to-digital converters (ADCs) in massive multiple-input multiple-output (MIMO) systems is promising to reduce the energy consumption. However, serious quantization errors limit the feasibility of high order quadrature amplitude modulation (QAM). This paper focuses on the performance analysis of 1-bit ADC massive MIMO systems with high order QAM. Firstly, we theoretically analyze the relationship between the quantization error and various quantization parameters. We reveal that there exists an overlapping of constellations at high signal to noise ratio (SNR) with symmetric quantization. This is because the amplitude information in the detected signal at high SNR is lost which is multiplied by the zero quantization threshold in the symmetric quantization. To overcome this problem, asymmetric quantization should be considered. Based on the analysis of the quantization error, we propose two approaches to recover the amplitude information. One is a near unbiased detection (NUD) by scaling the traditional linear detector and optimizing the quantization threshold. The other is a sub-array detection based on non-uniform quantization (SAD-NQ) to correct the deviation of the detection result by averaging over sub-arrays. Simulation results show that the proposed approaches can significantly improve the detection performance of high order QAM signal in the 1-bit ADC massive MIMO systems.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2023.3243121