NeTS: Small: Coordinated Beam Discovery, Association, and Handover in Ultra-Dense Millimeter Wave Cellular Networks

NeTS：小型：超密集毫米波蜂窝网络中的协调波束发现、关联和切换

• 批准号: 1718742
• 负责人: Danijela Cabric
• 金额: $ 50万
• 依托单位: University of California-Los Angeles
• 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 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1718742&HistoricalAwards=false
• 关键词: NeTS; Small; Coordinated; Beam; Discovery

Ever increasing demands for higher mobile data rates have resulted in exploration of new wireless technologies such as millimeter wave (mmWave) cellular networks due to large bandwidth availability at mmWave frequencies. However, higher channel propagation loss and higher probability of signal blockage in the mmWave band, as compared to the microwave band, have introduced challenges in establishing and maintaining the link between base stations and user equipment. In order to compensate for the losses, these devices use a large number of antennas and narrow beams to achieve high beamforming gains needed to establish the link. Further, ultra-dense base station deployment is needed to provide better coverage in the region. As a result, the mmWave cellular networks face new design challenges: i) establishing the link during initial channel access, ii) coordinated association of a user equipment to base stations and allocation of base station resources (beams and time) to users, and iii) beam adaptation for mobile user equipment and managing handovers in ultra-dense mobile networks. The proposed technologies are of fundamental importance to realize future ultra-dense 5G cellular networks, support user mobility and enable various applications requiring high data rate including video streaming, cloud computing, virtual reality, and augmented reality. This project will address these challenges and enable ultra-fast, low delay, and high throughput cellular networks in the mmWave band. First, it aims to develop an initial access procedure needed to establish the link between base stations and user equipment using compressive sensing measurements while considering practical hardware impairments. Next, it proposes to use the channel parameters obtained during the initial access to associate users with a specific base station and allocate resources accordingly. The novel association techniques will allow multiple base stations to simultaneously serve one user using independent RF chains, thereby increasing the data rate and reducing the probability of outage. Finally, a novel mobility management technique based on low-complexity beam-tracking and handover algorithms is proposed to enable seamless data transfer in ultra-dense mobile network. The proposed methodology will involve formulation of optimization framework for problems of coordinated beam association, resource allocation, and handovers and design of low complexity algorithms that solve the underlying optimization while enabling their practical realization.

由于毫米波频率的高带宽可用性，对更高移动数据速率的不断增长的需求导致了对诸如毫米波(毫米波)蜂窝网络等新无线技术的探索。然而，与微波频段相比，毫米波频段中更高的信道传播损耗和更高的信号阻塞概率给基站和用户设备之间的链路的建立和维护带来了挑战。为了补偿损耗，这些设备使用大量天线和窄波束来实现建立链路所需的高波束成形增益。此外，需要部署超高密度基站，以在该地区提供更好的覆盖。因此，毫米波蜂窝网络面临新的设计挑战：i)在初始信道接入期间建立链路，ii)协调用户设备与基站的关联并向用户分配基站资源(波束和时间)，以及iii)移动用户设备的波束适配和管理超密集移动网络中的切换。所提出的技术对于实现未来超密集的5G蜂窝网络、支持用户移动性以及支持各种需要高数据速率的应用，包括视频流、云计算、虚拟现实和增强现实，具有至关重要的基础作用。该项目将解决这些挑战，并在毫米波频段实现超快、低延迟和高吞吐量的蜂窝网络。首先，它的目标是制定在考虑实际硬件损伤的同时，使用压缩感测测量在基站和用户设备之间建立链路所需的初始接入程序。接下来，它建议使用在初始接入期间获得的信道参数来将用户与特定基站相关联，并相应地分配资源。新的关联技术将允许多个基站使用独立的RF链同时服务于一个用户，从而提高数据速率并降低中断的概率。最后，提出了一种新的基于低复杂度波束跟踪和切换算法的移动性管理技术，以实现超密集移动网络中的无缝数据传输。所提出的方法将包括建立协调波束关联、资源分配和切换问题的优化框架，并设计低复杂度的算法来解决潜在的优化问题，同时使其能够实际实现。

项目成果

mmRAPID: Machine Learning assisted Noncoherent Compressive Millimeter-Wave Beam Alignment

mmRAPID：机器学习辅助的非相干压缩毫米波光束对准

• 发表时间: 2020
• 期刊: ACM Mobicom
• 作者: Han Yan, Benjamin Domae

Fast Beam Training With True-Time-Delay Arrays in Wideband Millimeter-Wave Systems

• DOI: 10.1109/tcsi.2021.3054428
• 发表时间: 2021-04
• 期刊: IEEE Transactions on Circuits and Systems I: Regular Papers
• 作者: Veljko Boljanovic;Han Yan;Chung-Ching Lin;Soumen Mohapatra;D. Heo;Subhanshu Gupta;D. Cabric

Design of Millimeter-Wave Single-Shot Beam Training for True-Time-Delay Array

• DOI: 10.1109/spawc48557.2020.9154233
• 发表时间: 2020-02
• 期刊: 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
• 作者: Veljko Boljanovic;Han Yan;Erfan Ghaderi;D. Heo;Subhanshu Gupta;D. Cabric

Wideband channel tracking for mmWave MIMO system with hybrid beamforming architecture: (Invited Paper)

• DOI: 10.1109/camsap.2017.8313185
• 发表时间: 2017-12
• 期刊: 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
• 作者: Han Yan;S. Chaudhari;D. Cabric

Wideband Millimeter-Wave Beam Training with True-Time-Delay Array Architecture

采用真时延阵列架构的宽带毫米波束训练

• DOI: 10.1109/ieeeconf44664.2019.9048885
• 发表时间: 2019
• 期刊: and Computers
• 作者: Yan, Han;Boljanovic, Veljko;Cabric, Danijela
• 通讯作者: Cabric, Danijela