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

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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.