NeTS: Small: Collaborative Research: BRICK: Breaking the I/O and Computation Bottlenecks in Massive MIMO Base Stations

NeTS：小型：协作研究：BRICK：突破大规模 MIMO 基站的 I/O 和计算瓶颈

• 批准号: 1717559
• 负责人: Christoph Studer
• 金额: $ 25万
• 依托单位: Cornell University
• 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: 2017-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1717559&HistoricalAwards=false
• 关键词: NeTS; Small; Collaborative; Research; BRICK

Massive multi-antenna (MIMO) wireless systems, in which the base-station is equipped with hundreds or thousands of antenna elements, will enable unprecedented data rates, cell coverage, and transmission reliability compared to that of existing cellular communication systems. The presence of hundreds or thousands of radio-frequency (RF) transceivers and antennas, however, results in excessively high internal data rates, which results in chip-interconnect and computation bottlenecks that prevent a straightforward deployment of this technology in practice. This project will develop new technologies that rely on decentralized signal processing at the base-station in order to avoid these bottlenecks, which leads to feasible and scalable solutions that enable base-station designs with thousands of antenna elements without sacrificing performance or reliability. In addition to enabling massive MIMO in practice, the project will advance future cellular networks through collaboration with the telecommunications industry, with the Argos massive MIMO testbed, and other network research testbeds. The project's broader impact on education and outreach will include multiple components, including (i) training a diverse group of students as part of a collaborative, multi-institutional research team in the areas of communication theory and circuit design, (ii) integrating outcomes of the work into undergraduate and graduate courses, and (iii) making research outcomes broadly available through public-domain software packages and open-education resources via OpenStax courseware.The project develops novel decentralized algorithms as well as very-large scale integration (VLSI) and general-purpose computing on graphics processing units (GPGPU) architectures based on antenna clustering and parallelization, for the uplink (users communicate to base-station) and the downlink (base-station communicates to users). The main idea of decentralized baseband processing is to divide the signal-processing workload at the base-station into multiple computing fabrics that are each connected to only a subset of RF transceivers and antennas. To reduce the chip-interconnect and computation bottlenecks the project investigates (i) optimization-based algorithms that exchange consensus information among the antenna clusters and (ii) message-passing-based algorithms that avoid such consensus exchange altogether. The most promising algorithm solutions will be implemented on field-programmable gate array and GPGPU clusters to assess the efficacy and limits of the developed solutions with real-world performance, hardware, and bandwidth constraints. The results of this analysis will provide guidelines that enable optimal massive MIMO base-station designs that use decentralized baseband processing.

与现有的蜂窝通信系统相比，基本站配备了数百或数千个天线元件的大规模多腹地（MIMO）无线系统将使前所未有的数据速率，细胞覆盖率和传输可靠性能够实现。然而，数百或数千种射频（RF）收发器和天线的存在导致内部数据速率过高，这导致芯片间接连接和计算瓶颈，从而阻止了这种技术在实践中直接部署。该项目将开发新的技术，这些技术依赖于基础站点的分散信号处理，以避免这些瓶颈，从而导致可行且可扩展的解决方案，从而使基本站设计具有数千个天线元素而不牺牲性能或可靠性。除了在实践中启用大量的MIMO外，该项目还将通过与电信行业的合作以及Argos大量MIMO TestBED和其他网络研究台来推动未来的蜂窝网络。该项目对教育和宣传的更广泛影响将包括多个组成部分，包括（i）培训一组学生，这是在通信理论和巡回设计领域的协作，多机构研究团队的一部分，（ii）将工作结果整合到本科生和研究生课程中，并通过公共范围开放，并开放了开放式群体，并开放了开放式群体，并将其开放。分散化算法以及非常大的量表集成（VLSI）和图形处理单元（GPGPU）架构的通用计算基于天线聚类和并行化，用于上链接（用户与基础站通信）和下降链路（用户通信与用户）。分散基带处理的主要思想是将基本站位的信号处理工作负载分为多个计算织物，它们每个计算织物仅连接到RF收发器和天线的一个子集。为了减少芯片间接连接和计算瓶颈，该项目研究（i）基于优化的算法，这些算法在天线簇中交换共识信息，以及（ii）基于消息的基于消息的算法，避免了完全共识交换。最有希望的算法解决方案将在可进行现场编程的门阵列和GPGPU群集上实现，以评估具有现实性能，硬件和带宽约束的开发解决方案的效果和限制。该分析的结果将提供指南，以实现使用分散基带处理的最佳大型MIMO基站设计。

项目成果

Mismatched Data Detection in Massive MU-MIMO

大规模 MU-MIMO 中的不匹配数据检测

• DOI: 10.1109/tsp.2021.3121634
• 发表时间: 2021
• 期刊: IEEE Transactions on Signal Processing
• 影响因子: 5.4
• 作者: Jeon, Charles;Maleki, Arian;Studer, Christoph
• 通讯作者: Studer, Christoph

SMUL-FFT: A Streaming Multiplierless Fast Fourier Transform

SMUL-FFT：流式无乘法器快速傅立叶变换

• DOI: 10.1109/tcsii.2021.3064238
• 发表时间: 2021
• 期刊: IEEE Transactions on Circuits and Systems II: Express Briefs
• 作者: Mirfarshbafan, Seyed Hadi;Taner, Sueda;Studer, Christoph
• 通讯作者: Studer, Christoph

A Resolution-Adaptive 8 mm 2 9.98 Gb/s 39.7 pJ/b 32-Antenna All-Digital Spatial Equalizer for mmWave Massive MU-MIMO in 65nm CMOS

适用于 65nm CMOS 中毫米波大规模 MU-MIMO 的分辨率自适应 8 mm 2 9.98 Gb/s 39.7 pJ/b 32 天线全数字空间均衡器

• DOI: 10.1109/esscirc53450.2021.9567843
• 发表时间: 2021
• 期刊: IEEE 47th European Solid State Circuits Conference (ESSCIRC
• 作者: Castaneda, Oscar;Boynton, Zachariah;Mirfarshbafan, Seyed Hadi;Huang, Shimin;Ye, Jamie C.;Molnar, Alyosha;Studer, Christoph
• 通讯作者: Studer, Christoph

Optimality of the Discrete Fourier Transform for Beamspace Massive MU-MIMO Communication

• DOI: 10.1109/isit45174.2021.9518255
• 发表时间: 2021-07
• 期刊: 2021 IEEE International Symposium on Information Theory (ISIT)
• 作者: Sueda Taner;Christoph Studer

Sparse Beamspace Equalization for Massive MU-MIMO MMWave Systems

• DOI: 10.1109/icassp40776.2020.9052952
• 发表时间: 2020-03
• 期刊: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
• 作者: S. Mirfarshbafan;Christoph Studer