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Autonomous device-to-device communications for mission-critical internet-of-things

用于关键任务物联网的自主设备到设备通信

基本信息

批准号：
1786429
负责人：
金额：
--
依托单位：
Queen's University Belfast
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1786429
关键词：
Autonomous device communications mission critical

项目摘要

Internet of Things (IoT) market will reach $1.7 trillion by 2020, growing to 75 billion connected devices in 5 years. IoT technologies that allow literally billions of everyday objects to connect to each other over the internet have tremendous opportunities to enhance all of our lives. Within IoT, short-range device-to-device (D2D) communications promise to interconnect diverse devices with a significant increase in data traffics (a 1000-fold increase by 2020).Orthogonal frequency division multiplexing (OFDM) has been a key technology in the majority of modern wireless communication systems. Due to its robustness to multipath fading by transforming a frequency selective fading channel into parallel flat fading channels, OFDM has been adopted in the majority of current and future wireless communications standards such as IEEE 802.15.4 (smart utility network), IEEE 802.11 WiFi, and 4G LTE-A.The benefits of OFDM systems are not for free; they come at the cost of a loss of energy efficiency due to the distribution of finite power to multicarrier signals, an increased sensitivity to frequency offset and Doppler shift as well as transmission nonlinearity caused by the non-constant power ratio of OFDM signals. Such drawbacks challenge its direct application to D2D, especially in future healthcare or industrial communications that may integrate ultra-reliable connectivity with numerous IoT devices.With demands for high performance sensors, future D2D OFDM is challenged to increase the data rate much faster than today D2D. A large spectrum of tens of gigahertz (GHz) band (e.g., 60 GHz band) is allocated for future D2D in the 5G and this band is more than 200 times larger than today WiFi systems. However, larger channels, higher transmit power spending. For example, in 60 GHz band, 200 % of transmit power is needed, under line-of-sight propagation. This overhead challenges the direct use of today OFDM to a power-limited D2D. In addition, rapid developments in IoT power sensing/interpretation and intelligent algorithms have not been balanced by communications engineering principles. Today sensors comprise simple processors which communicate typically in open spaces to some central resource for further processing but in medical and unmanned factory applications, there is a need for more intelligent monitoring, multi-sensing cooperation processing by more multipath resilience monitoring devices which will be deployed dominantly in confined environments to communicate with sensors and central resource. This suggests the need for advanced, autonomous D2D platforms which offer high quality of performance at low power, but which can also be flexible and easily implemented.Main challenges are keen for D2D to bring autonomy with its flexible operation, improve the performance and concurrently offer low-complexity transceivers. It is vital especially for fully autonomous critical IoT systems. This points to increase need for advanced D2D techniques, offering high rate and reliability at very low power, particularly, in a highly dense environment, but which can be easily implemented.This project has four main objectives:(i) Creation of simpler, autonomous D2D realisation structure.(ii) Derivation of physical layer ultra-high reliability D2D in mission-critical IoTs.(iii) Integrated multiple access and D2D features to advance the performance of mission-critical IoT communications, in ultra-dense, and non-conventional fading environments.(iv) Realisation of more intelligent D2D using machine learning algorithms.Our goal is to provide theoretical references and guidelines for a successful autonomous D2D implementation in mission-critical IoT applications. Producing significant advance over classical D2D, the proposal will challenge how D2D is developed under a strict requirement in terms of reliability and energy by leveraging special multicarrier index keying algorithms and reducing its transceiver complexity.

到2020年，物联网（IoT）市场将达到1.7万亿美元，5年内将增长到750亿台连接设备。物联网技术允许数十亿日常物品通过互联网相互连接，这为改善我们所有人的生活提供了巨大的机会。在物联网中，短距离设备对设备（D2D）通信有望通过数据流量的显着增加（到2020年将增长1000倍）将各种设备互连起来。正交频分复用技术（OFDM）已成为现代无线通信系统中的一项关键技术。由于OFDM通过将频率选择性衰落信道转换为平行的平坦衰落信道，对多径衰落具有鲁棒性，因此在当前和未来的大多数无线通信标准中都采用了OFDM，如IEEE 802.15.4（智能公用事业网络）、IEEE 802.11 WiFi和4G LTE-A。OFDM系统的好处不是免费的；它们的代价是能量效率的损失，因为有限的功率分配给多载波信号，对频率偏移和多普勒频移的灵敏度增加，以及由OFDM信号的非恒定功率比引起的传输非线性。这些缺点挑战了其在D2D中的直接应用，特别是在未来可能与众多物联网设备集成超可靠连接的医疗保健或工业通信中。随着对高性能传感器的需求，未来的D2D OFDM面临着比现在的D2D更快地提高数据速率的挑战。为5G中的未来D2D分配了数十千兆赫（GHz）频段（例如60千兆赫频段）的大频谱，该频段比今天的WiFi系统大200多倍。然而，更大的信道，更高的传输功率消耗。例如，在60 GHz频段，在视距传播下，需要200%的发射功率。这种开销挑战了直接使用今天的OFDM到功率有限的D2D。此外，物联网功率传感/解释和智能算法的快速发展尚未得到通信工程原理的平衡。今天，传感器包括简单的处理器，通常在开放空间与一些中心资源进行通信以进行进一步处理，但在医疗和无人工厂应用中，需要更多的多路径弹性监测设备进行更智能的监测，多传感合作处理，这些设备将主要部署在受限环境中，与传感器和中心资源进行通信。这表明需要先进的自主D2D平台，以低功耗提供高质量的性能，但也可以灵活且易于实施。D2D面临的主要挑战是通过灵活的操作带来自主性，提高性能，同时提供低复杂性的收发器。这对于完全自主的关键物联网系统至关重要。这意味着对先进的D2D技术的需求增加，这种技术可以在非常低的功耗下提供高速率和可靠性，特别是在高密度环境中，但可以很容易地实现。该项目有四个主要目标：(i)创建更简单、自主的D2D实现结构。（ii）关键任务物联网中物理层超高可靠性D2D的推导。（iii）集成多址和D2D功能，以提高在超密集和非常规衰落环境下关键任务物联网通信的性能。（iv）使用机器学习算法实现更智能的D2D。我们的目标是为在关键任务物联网应用中成功实现自主D2D提供理论参考和指导。该提案在传统D2D的基础上取得了重大进展，将挑战D2D在可靠性和能量方面的严格要求，通过利用特殊的多载波索引键控算法并降低其收发器复杂性。