发表机构
TUBITAK BILGEM; Istanbul Technical University; Bilkent University（土耳其科学技术研究理事会信息与信息安全研究中心; 伊斯坦布尔理工大学; 比尔肯大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究分析大规模MIMO-OFDM系统在双量化下的上行频谱效率，推导了线性最小均方误差信道估计器，发现ADC与前传量化分辨率影响相当，低分辨率为主导限制因素，六位量化可达理想SE的90%以上。
AI 中文摘要
大规模多输入多输出（MIMO）系统通过在上行链路中使用大量接收天线来实现高频谱效率（SE）。然而，使用大量接收天线需要大量的模数转换器（ADC）以及较高的前传数据速率。低分辨率ADC可以降低功耗和成本，而前传量化可以降低所需的前传数据速率，但代价是在两个阶段都会引入量化失真。在宽带正交频分复用（OFDM）系统中，ADC量化在时域进行，而前传量化可在离散傅里叶变换之后应用，以仅传输有效子载波。在本研究中，我们探讨了在双量化和不完美信道估计条件下，前传链路上可实现的上行链路SE。我们根据双量化导频观测推导出线性最小均方误差信道估计器，并利用使用后遗忘界获得可实现的SE。数值结果表明，ADC和前传量化分辨率对可实现SE的影响相当。当两个分辨率不同时，较低的分辨率成为限制SE的主要因素。此外，我们的数值结果表明，六位ADC和前传量化可实现理想情况下SE的90%以上。
英文摘要
Massive multiple-input multiple-output (MIMO) achieves a high spectral efficiency (SE) by employing a large number of receive antennas in the uplink. Employing many receive antennas requires a large number of analog-to-digital converters (ADCs) and a high fronthaul data rate. Low-resolution ADCs can reduce power consumption and cost, while fronthaul quantization can reduce the required fronthaul data rate, at the expense of quantization distortion at both stages. In wideband orthogonal frequency-division multiplexing systems, ADC quantization is performed in the time domain, while fronthaul quantization may be applied after the discrete Fourier transform to transmit only active subcarriers. In this study, we investigate the achievable uplink SE over fronthaul links under double quantization and imperfect channel estimation. We derive a linear minimum mean-squared error channel estimator from the double-quantized pilot observations and obtain an achievable SE using the use-and-then-forget bound. Numerical results demonstrate that the ADC and fronthaul quantization resolutions have comparable impacts on the achievable SE. When the two resolutions differ, the lower resolution becomes the dominant factor limiting the SE. Furthermore, our numerical results show that six-bit ADC and fronthaul quantization achieve more than 90% of the SE attained in the ideal case.
