SBIR Phase I: Large Arrays for 5G MU-MIMO Wireless Access Operating in mm-wave Frequency Bands

SBIR 第一阶段：在毫米波频段运行的 5G MU-MIMO 无线接入大型阵列

• 批准号: 1722199
• 负责人: Sriramkumar Venugopalan
• 金额: $ 22.5万
• 依托单位: RF Pixels, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1722199&HistoricalAwards=false
• 关键词: SBIR; Phase; Large; Arrays; 5G

The commercial potential of this project lies in enabling much needed high wireless data rates and equal quality of service (QoS) to both densely populated areas as well as remote rural areas. 4G cellular and WiFi networks are facing a bottleneck due to proliferation of wireless devices and limited spectrum available in the currently allocated bands for wireless communications. Improving data connectivity would require new physical fiber to be laid out which is becoming impractical due to high costs vs. return on investment. The Federal Communications Commission has opened more spectrum in the mm-wave frequency spectrum (between 28-70 GHz) for mobile users to alleviate some of these issues. This project will enable spectrally efficient communication through frequency reuse for spatially separated mobile users in the mm-wave frequencies. It will also allow low cost dense deployment of 5G cellular base-stations to boost QoS. With this new paradigms in human machine interaction using machine learning can be advanced further. Remote educational programs, virtual and augmented reality (VR/AR) based learning, online health care and other new services around Internet of Things will be enhanced by better wireless connectivity. These technologies will uplift people?s lives delivering major economic and broad societal impact.This Small Business Innovation Research Phase I project proposes a revolutionary architecture that will enable massive multi-user MIMO techniques for mm-wave wireless systems to solve the spectrum scarcity issue. The mm-wave radio front end module (FEM) can reuse the same frequencies for spatially diverse mobile users with active beamforming thus enhancing the capacity of current cellular networks by 100x. A multitude of modules (1000s) will be used in a large array as a part of the mm-wave FEM making it crucial to achieve excellent power efficiency at the module level. This project will investigate a variant of Doherty power amplifier (PA) architecture to achieve highly efficient mm-wave transmitter. Module to module variation and within module variations can disturb accurate beamforming capability. Impact of these variations on forming coherent beams will be studied. A new method to calibrate a large array to tune out any module to module variation will be proposed through sufficient redundancies incorporated in the module design. Low sensitivity to calibration errors will be achieved while also trying to lower the calibration time. A new algorithm that achieves accurate simultaneous tracking of spatial mobile users to within 5-degrees using the new architecture will be proposed.

该项目的商业潜力在于为人口稠密地区和偏远农村地区提供急需的高无线数据速率和相同的服务质量 (QoS)。由于无线设备的激增以及当前分配的无线通信频段中可用的频谱有限，4G 蜂窝和 WiFi 网络正面临瓶颈。改善数据连接需要铺设新的物理光纤，由于成本与投资回报率较高，这变得不切实际。美国联邦通信委员会已在毫米波频谱（28-70 GHz 之间）中向移动用户开放更多频谱，以缓解其中一些问题。该项目将通过毫米波频率中空间分离的移动用户的频率复用实现频谱高效的通信。它还将允许低成本密集部署 5G 蜂窝基站，以提高服务质量。通过这种新的范例，使用机器学习的人机交互可以得到进一步发展。更好的无线连接将增强远程教育计划、基于虚拟和增强现实 (VR/AR) 的学习、在线医疗保健以及其他围绕物联网的新服务。这些技术将改善人们的生活，产生重大的经济和广泛的社会影响。这个小型企业创新研究第一阶段项目提出了一种革命性的架构，该架构将为毫米波无线系统提供大规模多用户 MIMO 技术，以解决频谱稀缺问题。毫米波无线电前端模块 (FEM) 可以通过主动波束成形为空间上不同的移动用户重复使用相同的频率，从而将当前蜂窝网络的容量提高 100 倍。作为毫米波 FEM 的一部分，将在大型阵列中使用多个模块（1000 个），这使得在模块级实现出色的功率效率至关重要。该项目将研究 Doherty 功率放大器 (PA) 架构的变体，以实现高效毫米波发射机。模块间的变化以及模块内的变化会干扰精确的波束形成能力。将研究这些变化对形成相干光束的影响。通过在模块设计中纳入足够的冗余，将提出一种校准大型阵列以消除任何模块之间差异的新方法。将实现对校准误差的低灵敏度，同时还尝试缩短校准时间。将提出一种新算法，使用新架构实现空间移动用户的精确同步跟踪，精度在 5 度以内。