Adaptive Communications Networks Research Group

This research group focuses on a range of networking architectures from mobile cellular systems to Internet of Things (IoT), ad-hoc sensor networks and vehicular networks. Techniques involve the design of advanced algorithms for improving network efficiencyand advanced digital systems for application-specific embedded systems. The Group uses state-of-the-art wireless and mobile network system level simulators and analytic tools for advanced network architecture and algorithm design/optimization, and dynamic field programmable gate array hardware to examine physical implementations of these principles.

Research Topics

Below are a range of research topics under which we are currently seeking collaboration from both academic and industry partners, and recruiting PhD students. If you are interested in colloboration or studying in any of these areas then please email the associated contact for further discussion.

4G/5G Mobile Cellular Systems and Technologies

According to a recent Cisco report, almost half a billion mobile devices and connections were added in 2016; mobile data traffic grew 18-fold over the past 5 years and is predicted to increase 7-fold within the next five years. There is a big gap between the capacity of mobile cellular networks and mobile data demands. Intensive research on the 5th generation (5G) cellular network architecture and technologies is undertaken to address the problem. At Aston we are actively researching the following 4G/5G topics:

  • Resource management and scheduling for ultra-dense small cells and heterogeneous networks
  • Device to device communications
  • Cross-layer design for power domain and code domain non-orthogonal multiple access
  • LTE assisted access (LAA) and cognitive radio: sharing unlicensed spectrum with non-cellular devices such as IEEE 802.11 devices.
  • Cloud radio access networks
  • Massive MIMO and millimeter wave technologies

Contact: Dr Jianhua He ([email protected]), Dr Zuoyin Tang ([email protected])

Internet of Things Systems and Technologies

Internet of Things(IoT) is the inter-working of physical devices (such as smart meters, buildings, vehicles). With recent advances of RFID, embedded electronics, wireless communications, physical devices can be easily connected and become smarter. These devices can be sensed and controlled remotely, creating enormous opportunities for direct integration of physical world into cyber space. IoT provide smartness on many sectors, such as transportation, environment monitoring, health care, water, energy, smart city and smart grid. It is expected by Cisco there will be 30 billion IoT devices by 2020 and these devices may generate more than two exabytes of data each day. The data can provide opportunities for big data analysis but also poses big challenges on data processing, transport and storage. The vulnerability of IoT devices also raise big concerns on the IoT security. As Aston we are working on the following IoT topics:

  • Mobile edge computing (MEC) architectures: The principle of MEC is moving computing closer to the edge, where IoT data is generated and analytics is needed. It can help alleviate the problems of data transport and real-time applications faced by traditional remote cloud based solutions. Fogs formed by dedicated computing devices and opportunistic computing devices can be used to undertake large scale data analytics. Embedded GPU computers can also be deployed to support.
  • MEC technologies: big data analytics with distributed computing engines (such as Spark) over both MEC and clouds. MEC is expected to complement with remote clouds. Proper admission control schemes and offloading schemes need to be designed to satisfy IoT data analytics requirements.
  • 5G and alternative low power communication technologies for IoT: provide efficient network access to massive IoT devices with NB-IoT from 3GPP and other technologies such as LORA for low power low data rate wide area wireless access.

Contact: Dr Jianhua He ([email protected]), Dr Zuoyin Tang ([email protected])

Connected Autonomous Vehicles

Road accidents are a global concern. More than 1.2 million people die each year on the roads due to road accidents, which also lead to severe traffic congestion. Existing road accident safety (RAS) systems including advanced driving assistance system (ADAS)/autonomous driving (AD) and connected vehicles (CV) have achieved huge interests and technology advances in the last several years. However both have inherent shortcomings and their safety performances are significantly limited due to isolated development and operation. Connected autonomous vehicles (CAV) is a new technology proposed to address the existing problems faced by ADAS/AD and CV, by combining ADAS/AD and CV. At Aston we are working on the following interesting topics:

  • Vehicle to everything (V2X) technology: V2X is a collective term referring to vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle to pedestrian (V2P). V2X is a core component of CAV system. Two mainstream V2X technologies are IEEE 802.11p and 3GPP LTE-V.
  • IEEE 802.11p is a variant of the general 802.11 technology tailed for vehicle connectivity. The nature of distributed random channel access in 802.11p offers high scalability and easy management, but also presents unpredictable quality of services (e.g. reliability and latency). 3GPP LTE-V is promising with large coverage, centralized management and high efficiency, but there are also many open research issues to be solved before it can be applied to CV, such as D2D resource allocation for V2V with low latency and high reliability.
  • Advanced object detection and cooperation: detection of objects (such as vehicles, pedestrians and cyclists) is critical for ADAS and AD. Even with advanced sensors such as Lidar and high resolution cameras, accidents are still likely to happen. Fast and efficient deep neural networks based models and technologies are developed for practical application to ADAS with improved driving object detection performance. In addition, driving hazards are detected and shared with neighbour drivers via V2X to enable cooperative driving. Cooperative road safety applications such as forward car collision avoidance (FCCA) and forward pedestrian collision avoidance (FPCA) can be effectively supported.

 Contact: Dr Jianhua He ([email protected]), Dr Zuoyin Tang ([email protected])

Ad-hoc networks

Ad-hoc networks are dynamic in that nodes on the network can join and leave at any time as well as being able to move while connected. Thus the network topology and hence the routing tables are dynamic. This can happen on slow time scales (i.e. the topology changes more slow than the time it takes to update the routes) where traditional approaches will work. If the topology changes on a time scale that is comparable or faster than the routing update time then new approaches are needed. Contact: Prof. Keith Blow

Applications of FPGAs

FPGAs have evolved from high cost prototyping hardware solutions into low cost mainstream products. The main reason is the ability to reconfigure these devices after the hardware has been built and thus facilitate rapid product development and capability upgrades. The research focuses on the use of FPGAs to implement entire microcontroller architectures on these devices in VHDL. Contact: Dr. Marc Eberhard

Architectures for handling high-speed serial data.

High speed serial data interconnects are becoming more and more important for future high performance computing cluster technologies. Both latency and throughput are essential and the research work focuses on using FPGAs to implement high performance switch fabrics and backbones. Contact: Dr. Marc Eberhard

Massively parallel simulations of fibre optic communication systems including HPC scalability studies.

In fibre optic communication systems the study of rare events is of great importance to derive reliable estimates of outage and error probabilities. The research focuses on using supercomputers with thousands of cores to run these massively parallel simulations and to develop the simulation software used. Contact: Dr. Marc Eberhard

Research Studentships

Funded studentships, which are typically restricted to UK/EU citizens, are advertised on the University and School websites when they are available. Applicants from outside the EU may apply for the studentships but will need to pay the difference between the ‘Home/EU’ and the ‘Overseas’ tuition fees. Formal applications should be made through online-application or by contacting the Research Admission Officer ([email protected]) at School of Engineering and Applied Science. 

Research Degrees at Aston

Research Degrees at Aston

Find out more about the different Research degrees available at Aston.

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How to Apply

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