NeTS: Small: Collaborative Research: Improving Spectrum Efficiency for Hyper-Dense IoT Networks

新兴的物联网(IoT)技术将实现一系列全新的应用，对社会的许多方面产生深远的影响，包括卫生管理、交通运输、农业、安全和应急以及灾难应对。与此同时，物联网部署的大规模增长给无线行业的成功运营带来了几个巨大的挑战。该项目旨在开发新的物联网架构和算法，以实现大规模物联网部署。特别是，通过三个学术机构和业界的密切合作，拟议的研究将通过引入整体、跨层的设计框架和协议来取得进展，以提高大规模物联网网络的频谱/能量效率和延迟。研究成果将支持新兴的标准化活动，以支持下一代无线网络中的物联网。本项目旨在解决以下挑战：1)面向海量物联网的以系统为中心的波形设计：研究人员将结合随机几何技术和载波波形的模糊函数进行系统容量分析，比较候选波形的部署适宜性，开发适合大规模物联网部署的联合均衡器和波形设计，并提出具有良好频谱效率、抗干扰和延迟特性的新波形。2)基于图形的无线资源管理：明智的无线资源管理对于超密集物联网网络的正常运行至关重要。该项目将利用图论中的加权划分和匹配工具来开发波形感知的动态资源分配方案，以抑制不同无线物联网链路之间的相互干扰，并提高单跳和多跳大规模物联网部署中的频谱利用效率。3)核心网连接效率：海量物联网接入核心网功能没有考虑物联网流量特性，需要重新思考。该项目将开发和严格研究基于聚合的连接模型，以管理使用相同资源(即承载)的多个物联网设备流量。对于共享相同连接的物联网设备的有效分组，研究人员将使用高效的进化聚类方法，同时优先考虑在早期推动中获得的干扰最小化的组。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The emerging Internet of Things (IoT) technology will enable a whole new set of applications, imposing far reaching influence on many aspects of society, including management of health, transportation, agriculture, safety and emergency and disaster response. At the same time, the massive growth of IoT deployments poses several grand challenges to the wireless industry for their successful operation. This project aims to develop novel IoT architectures and algorithms to enable large-scale IoT deployments. In particular, through close collaboration of three academic institutions and industry, the proposed research will make advances by introducing holistic, cross-layer design framework and protocols for improving spectral/energy efficiency and latency of massive IoT networks. The research outcomes will support emerging standardization activities to enable IoT in next-generation wireless networks. This project aims at tackling the following challenges: 1) System-Centric Waveform Design for Massive IoT: The researchers will couple stochastic geometry techniques and ambiguity functions of carrier waveforms to perform system-wide capacity analysis, compare waveform candidates for deployment suitability, develop joint equalizer and waveform designs for massive IoT deployments, and propose new waveforms having a good spectral efficiency, interference resilience, and latency characteristics. 2) Graph-based Radio Resource Management: Judicious radio resource management is critical to the proper functioning of hyper-dense IoT networks. The project will exploit weighted partitioning and matching tools from graph theory to develop waveform-aware dynamic resource allocation schemes to suppress mutual interference among a diverse set of wireless IoT links and improve spectrum utilization efficiency in single-hop and multi-hop massive IoT deployments. 3) Core network Connection Efficiency: Rethinking the core network functions for connection of massive IoT is required as they are not designed considering the IoT traffic characteristics. The project will develop and rigorously study an aggregation based connectivity model to manage multiple IoT device traffic using the same resources (i.e., bearers). For efficient groupings of the IoT devices that will share the same connection, researchers will use efficient evolutionary clustering methods, while giving preference to the interference minimizing groups obtained in earlier thrusts.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.