The Machine-To-Machine (M2M) applications of Wireless Sensor Networks (WSNs) and Wireless Body Area Networks (WBANs) are set to offer many new capabilities in the EPSRC themes of 'Healthcare technologies', 'Living with environmental change' and 'Global uncertainties', granting significant societal and economic benefits. These networks comprise a number of geographically-separated sensor nodes, which collect information from their environment and exchange it using wireless transmissions. However, these networks cannot as yet be employed in demanding applications, because current sensor nodes cannot remain powered for a sufficient length of time without employing batteries that are prohibitively large, heavy or expensive. In this work, we aim to achieve an order-of-magnitude extension to the battery charge-time of WSNs and WBANs by facilitating a significant reduction in the main cause of their energy consumption, namely the energy used to transmit information between the sensor nodes. A reduction in the sensor nodes' transmission energy is normally prevented, because this results in corrupted transmitted information owing to noise or interference. However, we will maintain reliable communication when using a low transmit energy by specifically designing channel code implementations that can be employed in the sensor nodes to correct these transmission errors. Although existing channel code implementations can achieve this objective, they themselves may have a high energy consumption, which can erode the transmission energy reduction they afford. Therefore, in this work we will aim for achieving a beneficial step change in the energy consumption of channel code implementations so that their advantages are maintained when employed in energy-constrained wireless communication systems, such as the M2M applications of WSNs and WBANs. We shall achieve this by facilitating a significant reduction in the supply voltage that is used to power the channel code implementations. A reduction in the supply voltage is normally prevented, because this reduces the speed of the implementation and causes the processed information to become corrupted, when its operations can no longer be performed within the allotted time. However, we will maintain reliable operation when using a low supply voltage, by specifically designing the proposed channel code implementations to use their inherent error correction ability to correct not only transmission errors, but also these timing errors. To the best of our knowledge, this novel approach has never been attempted before, despite its significant benefits. Furthermore, we will develop methodologies to allow the designers of WSNs and WBANs to estimate the energy consumption of the proposed channel code implementations, without having to fabricate them. This will allow other researchers to promptly optimise the design of the proposed channel code implementations to suit their energy-constrained wireless communication systems, such as WSNs and WBANs. Using this approach, we will demonstrate how the channel coding algorithm and implementation can be holistically designed, in order to find the most desirable trade-off between complexity and performance.

It is reported that the total energy consumed by the ICT infrastructure of wireless and wired networks takes up over 3 percent of the worldwide electric energy consumption that generated 2 percent of the worldwide CO2 emissions nowadays. It is predicted that in the future a major portion of expanding traffic volumes will be in wireless side. Furthermore, future wireless network systems (e.g., 4G/B4G) are increasingly demanded as broadband and high-speed tailored to support reliable Quality of Service (QoS) for numerous multimedia applications. With explosive growth of high-rate multimedia applications (e.g. HDTV and 3DTV), more and more energy will be consumed in wireless networks to meet the QoS requirements. Specifically, it is predicted that footprint of mobile wireless communications could almost triple from 2007 to 2020 corresponding to more than one-third of the present annual emissions of the whole UK. Therefore, energy-efficient green wireless communications are paid increasing attention given the limited energy resources and environment-friendly transmission requirements globally. The aim of this project is to improve the joint spectrum and energy efficiency of future wireless network systems using cognitive radio technology along with innovative game-theoretic resource scheduling methods, efficient cross-layer designs and contemporary clinical findings. We plan to consider the health and environmental concerns to introduce power-efficient resource scheduling designs that intelligently exploit the available wireless resources in next-generation systems. Our efforts will leverage applications of cognitive radio techniques to situational awareness of the communications system with adaptive power control and dynamic spectrum allocation. This project will underpin the UK green communication technology by designing environment-friendly joint power and spectrum efficient wireless communication systems.