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同等的服务质量(Qos)。由于无线设备的激增和当前分配的无线通信频段可用频谱有限，4G蜂窝和WiFi网络正面临瓶颈。改善数据连通性将需要铺设新的物理光纤，但由于高成本与投资回报相比，这变得不切实际。联邦通信委员会已经为移动用户开放了更多毫米波频谱(28-70 GHz)，以缓解其中一些问题。该项目将通过在毫米波频率上对空间上分离的移动用户进行频率再利用来实现频谱高效通信。它还将允许低成本密集部署5G蜂窝基站，以提高服务质量。有了这种新的范例，使用机器学习的人机交互可以进一步发展。围绕物联网的远程教育程序、基于虚拟和增强现实(VR/AR)的学习、在线医疗和其他新服务将通过更好的无线连接得到增强。这些技术将提升人们？S的生活带来了重大的经济和广泛的社会影响。这个小企业创新研究第一阶段项目提出了一个革命性的架构，将使毫米波无线系统的大规模多用户MIMO技术能够解决频谱短缺问题。毫米波无线电前端模块(Fem)可以对空间不同的移动用户重复使用相同的频率，进行主动波束形成，从而将当前蜂窝网络的容量提高100倍。多个模块(1000个)将作为毫米波有限元的一部分在大阵列中使用，因此在模块级别实现出色的功率效率至关重要。本项目将研究Doherty功率放大器(PA)结构的一种变体，以实现高效的毫米波发射机。模块之间的变化和模块内的变化会干扰准确的波束形成能力。这些变化对形成相干光束的影响将被研究。通过在模块设计中加入足够的冗余，将提出一种新的方法来校准大阵列以排除任何模块到模块的变化。在尝试缩短校准时间的同时，将实现对校准误差的低灵敏度。提出了一种新的算法，利用新的架构实现了对空间移动用户的精确同步跟踪，跟踪精度在5度以内。