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

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，短距离设备到设备（D2 D）通信有望互连各种设备，数据流量显著增加（到2020年将增加1000倍）。正交频分复用（OFDM）已经成为大多数现代无线通信系统中的关键技术。由于OFDM通过将频率选择性衰落信道变换为并行平坦衰落信道而对多径衰落具有鲁棒性，因此OFDM已被采用于大多数当前和未来的无线通信标准中，诸如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;它们的代价是由于有限功率分配给多载波信号而导致的能量效率损失、对频率偏移和多普勒频移的敏感性增加以及由OFDM信号的非恒定功率比引起的传输非线性。这些缺点使其直接应用于D2 D面临挑战，特别是在未来的医疗保健或工业通信中，这些通信可能与众多物联网设备集成超可靠的连接。随着对高性能传感器的需求，未来的D2 D OFDM面临的挑战是比现在的D2 D更快地提高数据速率。数十千兆赫（GHz）频带的大频谱（例如，60 GHz频带）被分配用于5G中的未来D2 D，并且该频带比今天的WiFi系统大200倍以上。然而，更大的信道，更高的发射功率消耗。例如，在60 GHz频带中，在视距传播下需要200%的发射功率。这种开销挑战了当今OFDM对功率受限的D2 D的直接使用。此外，物联网功率感测/解释和智能算法的快速发展尚未与通信工程原理相平衡。今天的传感器包括简单的处理器，其通常在开放空间中与一些中央资源通信以进行进一步处理，但是在医疗和无人工厂应用中，需要通过更多的多径弹性监测设备进行更智能的监测、多传感协作处理，所述多径弹性监测设备将主要部署在受限环境中以与传感器和中央资源通信。这表明需要先进的自主D2 D平台，其在低功耗下提供高质量的性能，但也可以是灵活的和容易实现的。D2 D的主要挑战是通过其灵活的操作带来自主性，提高性能并同时提供低复杂度的收发器。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D2 D技术的需求增加，特别是在高度密集的环境中，以非常低的功耗提供高速率和可靠性，但可以轻松实现。该项目有四个主要目标：（i）创建更简单的自主D2 D实现结构。(ii)关键任务IoT中物理层超高可靠性D2 D的推导。(iii)集成的多址接入和D2 D功能可在超密集和非传统衰落环境中提升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D2 D。我们的目标是为关键任务物联网应用中成功实现自主D2 D提供理论参考和指导。该提案相对于经典D2 D产生了显著的进步，将挑战如何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度来在可靠性和能量方面的严格要求下开发D2 D。

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.