采用低分辨率ADC的Massive MIMO上行链路误码率性能

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摘要翻译：
大规模多输入多输出(MIMO)技术是下一代无线通信系统(5G)的发展方向。在该技术中，基站(BS)配备了大量的天线。对所有天线使用高分辨率模数转换器可能会导致BS的高成本和高功耗。通过对不同检测技术(MMSE，ZF)和不同调制方式(QPSK，16-QAM)的误码率(BER)性能进行分析，以找到最佳量化分辨率，并通过数值计算，对低分辨率ADC在massive MIMO上行链路中的应用进行了评估。我们的结果表明，在massive MIMO上行链路系统中，使用几位分辨率ADC的误码率性能与使用全精度ADC的情况相当。我们发现量化电平（ADC中的比特数）的最佳选择取决于调制技术和BS上的天线数。
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英文标题：
《BER Performance of Uplink Massive MIMO With Low-Resolution ADCs》
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作者：
Azad Azizzadeh, Reza Mohammadkhani, Seyed Vahab Al-Din Makki
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最新提交年份：
2017
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  Massive multiple-input multiple-output (MIMO) is a promising technology for next generation wireless communication systems (5G). In this technology, Base Station (BS) is equipped with a large number of antennas. Employing high resolution analog-to-digital converters (ADCs) for all antennas may cause high costs and high power consumption for the BS. By performing numerical results, we evaluate the use of low-resolution ADCs for uplink massive MIMO by analyzing Bit Error Rate (BER) performance for different detection techniques (MMSE, ZF) and different modulations (QPSK, 16-QAM) to find an optimal quantization resolution. Our results reveal that the BER performance of uplink massive MIMO systems with a few-bit resolution ADCs is comparable to the case of having full precision ADCs. We found that the optimum choice of quantization level (number of bits in ADCs) depends on the modulation technique and the number of antennas at the BS.
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PDF链接：
https://arxiv.org/pdf/1710.00335

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关键词：massive mass mas SIV IMO 误码率 找到 可能 Massive high