| EPSRC Reference: |
EP/X04047X/1 |
| Title: |
Platform Driving The Ultimate Connectivity |
| Principal Investigator: |
Haas, Professor H |
| Other Investigators: |
| Zheng, Professor G |
Chen, Professor Y |
Sellathurai, Professor M |
| Leung, Professor KK |
Penty, Professor R |
Elmirghani, Professor J |
| Richardson, Professor DJ |
Simeonidou, Professor D |
Thompson, Professor JS |
| Tang, Professor J |
Petropoulos, Professor P |
Matthaiou, Professor M |
| Popoola, Professor WO |
Yang, Dr Y |
Liu, Dr Y |
| Ngo, Dr H |
Vlaski, Dr S |
Hussain, Dr R |
| Elgorashi, Dr T |
Mahmoodi, Professor T |
Musavian, Professor L |
| Cotton, Professor S |
Nallanathan, Professor A |
Ling, Dr C |
| Safari, Professor M |
Nejabati, Professor R |
Hanzo, Professor L |
| Dawson, Professor M |
O'Brien, Professor D |
Lambotharan, Professor S |
| El-Hajjar, Dr M |
Nakhai, Dr MR |
Savory, Professor SJ |
| Thomos, Professor N |
Derakhshani, Dr M |
Deng, Dr Y |
| Herrnsdorf, Dr JHL |
Yan, Dr S |
Tavakkolnia, Dr I |
| Vasilakos, Dr X |
Clerckx, Professor B |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Electronic and Electrical Engineering |
| Organisation: |
University of Strathclyde |
| Scheme: |
Standard Research - NR1 |
| Starts: |
01 May 2023 |
Ends: |
31 March 2024 |
Value (£): |
2,030,861
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| EPSRC Research Topic Classifications: |
| Networks & Distributed Systems |
RF & Microwave Technology |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
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Summary on Grant Application Form |
The research of the TITAN platform is geared towards the ultimate network of networks and is structured in six strongly interconnected lighthouse projects which reflect all network elements - 1) the core, 2) optical fibre, 3) radio frequency (RF) including cellular and wireless networks, 4) emerging optical wireless networks for access and backhaul, 5) non-terrestrial networks involving satellites, aerial and underwater networks, and finally 6) quantum communication networks.
The research on the core network focuses on a new architecture and artificial intelligence (AI) techniques that enable the integration of multi-access technologies for a seamless end-to-end service delivery by considering advanced requirements in terms of data rate, latency, security and energy efficiency. TITAN will conduct novel research that aims at orchestrating the different existing and emerging RF networks (3G, 4G, 5G, 6G, WiFi, Bluetooth, etc.) towards a single network by developing techniques that would optimally select the respective RF network, or networks, and develop the respective protocols to enable a seamless end-to-end connection. Because of the undisputed need for new spectrum in future networks, TITAN will crucially include new networks that are built around the terahertz and optical spectrum. Since these networks will benefit from new intelligent reflecting surfaces as part of a new network element, TITAN will include research on the networking aspects and the integration of reconfigurable intelligent surfaces (RIS) by building on the work on AI and machine learning (ML) developed for other parts of the network, such as edge and core. Optical fibre networks are an important element of a network of networks. Therefore, TITAN will address research questions on the optimum integration of advanced optical fibre technologies such as hollowcore fibres and new agile transceiver technologies to support key network requirements such as latency. Universal service availability and what is described as the 'digital divide' represent an increasing societal challenge. Therefore, TITAN will conduct critical research on the integration of non-terrestrial networks which include aerial, satellite and underwater networks all geared towards a seamless end-to-end service provision which is achieved by the holistic approach of TITAN. Lastly, TITAN will meaningfully integrate new quantum network technologies alongside conventional networks and will provide important guidance on the optimum use of both fundamental networks. An important consideration of TITAN is the extraction of sensing information from networks. All network elements have particular features and, in conjunction with ML techniques, important side information can be extracted. TITAN will investigate this capability for each network segment, but crucially brings the independent sensing information together to achieve an ultra-cognitive network which exhibits the highest level of self-x (configuration, healing, automation, optimisation).
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.strath.ac.uk |