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CIF: Small: Massive MIMO for Massive Machine-Type Communication

CIF：小型：用于大规模机器类型通信的大规模 MIMO

基本信息

批准号：
1814803
负责人：
Xiaodong Wang
金额：
$ 49.99万
依托单位：
Columbia University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-10-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1814803&HistoricalAwards=false
关键词：
CIF Small Massive MIMO Machine

项目摘要

The objective of this project is to investigate massive multiple-input multiple-output (MIMO) coding and signal processing techniques for massive machine-type communications, which is an important scenario in the emerging 5G wireless systems. Key features of the massive machine-type communication system include the massive device connectivity and the sporadic device activity pattern. The massive MIMO technique is well suited for accommodating a large number of devices and maintaining a constant level of energy efficiency that is independent of the number of devices. In addition to the potential technical impacts, the investigators plan to incorporate the research into graduate and undergraduate curricula and to also develop summer projects to facilitate K-12 outreach.This project considers the uplink of a massive machine-type communication system consisting of a base station equipped with a large number of antennas, as well as a large number of potential device nodes, out of which a fraction are active at any given time. On the transmitter side, to address the shortage of orthogonal pilot sequences when the number of devices is large, multi-base codes will be designed that contain a large number of orthogonal subsets of vectors. To address the high-complexity of device activity detection when the number of nodes is large, pilot sequences based on various codes and Grassmannian modulation constellations will be designed that can be decoded efficiently with complexity independent of the number of nodes. On the receiver side, joint device activity detection and channel estimation will be developed by exploiting the sparsity in both device activity and the channel structures. Moreover, when the base station employs a smaller number of radio frequency chains compared with the antenna size, matrix or tensor completion techniques will be developed for channel estimation or data decoding in the presence of missing data, by exploiting the low-rank property of the received signals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的目标是研究大规模机器类型通信的大规模多输入多输出（MIMO）编码和信号处理技术，这是新兴5G无线系统中的一个重要场景。大规模机器型通信系统的主要特征包括大规模设备连接和零星设备活动模式。大规模MIMO技术非常适合容纳大量设备，并保持与设备数量无关的恒定能源效率水平。除了潜在的技术影响外，研究人员还计划将这项研究纳入研究生和本科课程，并开发夏季项目，以促进K-12的推广。本项目考虑的是一个大型机器型通信系统的上行链路，该系统由一个配备了大量天线的基站以及大量潜在的设备节点组成，其中一部分在任何给定时间都是活动的。在发射端，为了解决设备数量较大时正交导频序列不足的问题，需要设计包含大量正交向量子集的多基码。为了解决节点数较大时设备活动检测的高复杂性问题，将设计基于各种编码和格拉斯曼调制星座的导频序列，该导频序列可以有效解码，且复杂度与节点数无关。在接收端，通过利用设备活动和信道结构的稀疏性，将开发联合设备活动检测和信道估计。此外，与天线尺寸相比，当基站采用较少数量的射频链时，将开发矩阵或张量补全技术，通过利用接收信号的低秩特性，在存在缺失数据的情况下进行信道估计或数据解码。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。