CNS Core: Small: Supporting Massive Wireless Connections in the Internet-of-Things (IoT) with Multiple Zadoff-Chu (MZC) sequences

CNS 核心：小型：通过多个 Zadoff-Chu (MZC) 序列支持物联网 (IoT) 中的大规模无线连接

• 批准号: 1910268
• 负责人: Zhenghao Zhang
• 金额: $ 44.68万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910268&HistoricalAwards=false
• 关键词: CNS; Core; Small; Supporting; Massive

In this project, a novel wireless Low Power Wide Area Network (LPWAN) technology, referred to as MZC, for Multiple Zadoff-Chu, will be designed. LPWAN is a crucial component in Internet of Things (IoT), which will improve everyday life and business efficiency. IoT depends on LPWAN technologies to maintain connections to the devices, which face unprecedented challenges, because the communication range may be long, the number of devices may be very large, and the devices may rely on a single battery for years. MZC will offer significant advantages over existing solutions in network capacity, speed, communication range, and power consumption. Preliminary experimental results show that MZC outperforms LoRa, a leading LPWAN technology, using less than one-eighth of the bandwidth resource, as well as much lower signal power, which suggests that MZC will achieve over 8 times the network capacity and a longer communication range or a longer battery life. Given its potential benefit, MZC will become a very strong contender and may potentially reshape the LPWAN technology landscape. This project will advance the knowledge on fundamental issues in wireless communication and networking in the very low Signal to Noise Ratio (SNR) regime. Results obtained in this project will be used in related classes. Undergraduate students and students from underrepresented and minority groups will be actively recruited. MZC is motivated by the excellent properties of the Zadoff-Chu (ZC) sequence, which have been used and proven in LTE (Long Term Evolution) networks. In MZC, a transmitted ZC sequence will generate a peak at the receiver, the location and phase of which can be used to modulate data. A number of tasks will be investigated, with the goal of optimizing the design at every layer, and implementing a functional prototype to facilitate the transition to practice. In particular, first, the physical layer will be further optimized with better methods and error correction codes to cope with signal degradation and error caused by practical issues such as synchronization error and carrier frequency offset. Second, a hybrid Medium Access Control (MAC) layer will be designed, which has both a scheduled access method and a random access method, the latter based on a novel scheme called Peak Location Division Multiple Access (PLDMA). Third, core problems in the networking layer will be solved to maximize the overall network capacity, exploiting the low interference among ZC sequences with different roots, which allows nodes to use the same frequency channel without causing significant interferences.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.

在这个项目中，将设计一种新的无线低功率广域网（LPWAN）技术，称为MZC，用于多个Zadoff-Chu。LPWAN是物联网（IoT）的重要组成部分，将提高日常生活和业务效率。物联网依靠LPWAN技术来维持与设备的连接，这面临着前所未有的挑战，因为通信范围可能很长，设备数量可能非常大，并且设备可能多年依赖单个电池。与现有解决方案相比，MZC在网络容量、速度、通信范围和功耗方面具有显著优势。初步实验结果表明，MZC使用不到八分之一的带宽资源，以及更低的信号功率，优于领先的LPWAN技术LoRa，这表明MZC将实现超过8倍的网络容量，更长的通信范围或更长的电池寿命。鉴于其潜在的优势，MZC将成为一个非常强大的竞争者，并有可能重塑LPWAN技术的格局。该项目将促进对极低信噪比（SNR）体制下无线通信和网络基本问题的认识。本课题的研究结果将用于相关课程。将积极招收本科生和来自代表性不足和少数群体的学生。MZC是由Zadoff-Chu （ZC）序列的优良特性所驱动的，该序列已在LTE（长期演进）网络中得到应用和验证。在MZC中，发送的ZC序列将在接收器处产生一个峰值，该峰值的位置和相位可用于调制数据。我们将研究许多任务，以优化每一层的设计为目标，并实现一个功能原型，以促进向实践的过渡。特别是，首先，物理层将进一步优化，采用更好的方法和纠错码，以应对同步误差和载波频偏等实际问题导致的信号退化和误差。其次，设计混合介质访问控制（MAC）层，该层具有调度访问方法和随机访问方法，随机访问方法基于峰值定位分多址（PLDMA）。第三，解决网络层的核心问题，最大限度地提高网络的整体容量，利用不同根的ZC序列之间的低干扰，使节点使用同一频率信道而不会产生明显的干扰。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。

项目成果

ZCNET: Achieving High Capacity in Low Power Wide Area Networks

• DOI: 10.1109/tnet.2022.3158482
• 发表时间: 2022-10
• 期刊: IEEE/ACM Transactions on Networking
• 作者: Zhenghao Zhang;Raghav Rathi;Steven Perez;Jumana Bukhari;Yaoguang Zhong

Novel Access Methods in Cellular Networks Based on the Analog Bloom Filter

• DOI: 10.1109/twc.2023.3235650
• 发表时间: 2023-08
• 期刊: IEEE Transactions on Wireless Communications
• 影响因子: 10.4
• 作者: Zhenghao Zhang;Raghav Rathi

TnB: resolving collisions in LoRa based on the peak matching cost and block error correction

• DOI: 10.1145/3555050.3569132
• 发表时间: 2022-11
• 期刊: Proceedings of the 18th International Conference on emerging Networking EXperiments and Technologies
• 作者: Raghav Rathi;Zhenghao Zhang

MPCast: A Novel Downlink Transmission Technology for Low Power Wide Area Networks

MPCast：一种用于低功耗广域网的新型下行链路传输技术

• DOI: 10.1109/icc42927.2021.9500584
• 发表时间: 2021
• 期刊: ICC 2021 - IEEE International Conference on Communications
• 作者: Zhang, Zhenghao