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

• 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; CIF; Small; Massive; MIMO; Machine

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.

该项目的目的是研究大规模的机器型通信的大量多输入多输出（MIMO）编码和信号处理技术，这是新兴5G无线系统中的重要情况。庞大的机器类型通信系统的关键特征包括庞大的设备连接和零星的设备活动模式。庞大的MIMO技术非常适合容纳大量设备，并保持恒定的能源效率，而能源效率与设备数量无关。 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.在发射器侧，要解决较大的设备数量时，将设计多个矢量的正交子集时，要解决正交试点序列的短缺。为了解决当节点数量较大时，将设计基于各种代码和Grassmannian调制星座的试验序列时，可以设计出可以有效地用与节点数量的复杂性来有效地解码的。 在接收器侧，将通过利用设备活动和通道结构中的稀疏性来开发关节设备活动检测和通道估计。此外，当基站使用较少的射频链与天线尺寸相比，将开发矩阵或张量的完成技术，以供渠道估算或在缺少数据的存在下进行数据解码，通过利用接收到的信号的低排名属性，这是NSF奖励的法定任务，反映出值得评估的构成者，这是由Infactiac and Intelliatial构成的。