Loading...
Projects / Programmes source: ARIS

Advanced Ray-Tracing Techniques in Radio Environment Characterization and Radio Localization

Research activity

Code Science Field Subfield
2.08.00  Engineering sciences and technologies  Telecommunications   

Code Science Field
T180  Technological sciences  Telecommunication engineering 

Code Science Field
2.02  Engineering and Technology  Electrical engineering, Electronic engineering, Information engineering 
Keywords
radio signal prediction, ray tracing, indoor localization, sensor networks, cloud computing
Evaluation (rules)
source: COBISS
Researchers (12)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  35934  PhD Klemen Bregar  Telecommunications  Junior researcher  2016 - 2019  36 
2.  29550  PhD Matic Herman  Communications technology  Researcher  2016 - 2017  11 
3.  26025  PhD Andrej Hrovat  Telecommunications  Researcher  2016 - 2019  230 
4.  07109  PhD Tomaž Javornik  Telecommunications  Researcher  2016 - 2019  435 
5.  05209  PhD Gorazd Kandus  Telecommunications  Retired researcher  2016 - 2019  556 
6.  50991  Jože Kulovic  Computer science and informatics  Researcher  2018 - 2019 
7.  15087  PhD Mihael Mohorčič  Telecommunications  Head  2016 - 2019  476 
8.  12765  PhD Roman Novak  Telecommunications  Researcher  2016 - 2019  143 
9.  09856  PhD Igor Ozimek  Computer science and informatics  Researcher  2016 - 2019  178 
10.  17166  PhD Gregor Pipan  Interdisciplinary research  Researcher  2016 - 2019  44 
11.  26466  Miha Smolnikar  Telecommunications  Researcher  2016 - 2019  100 
12.  21555  PhD Marjan Šterk  Computer science and informatics  Researcher  2016 - 2019  69 
Organisations (2)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  90,706 
2.  2012  XLAB software development and consulting Ltd.  Ljubljana  1639714  322 
Abstract
Next generation wireless networks will have to be aware of and adapt to their exact operating environment in real time in order to meet the requirements for significantly higher throughput at lower energy consumption and increased utilisation of radio resources. Current methods of radio environment characterisation and their implementations still do not fulfill these requirements. In the proposed project the radio ray tracing method, the telecommunication counterpart of the well-known rendering technique in computer graphics, will be revisited from the algorithmic point of view with the aim to use it for characterisation of dynamic radio environments. New concepts, such as the radio ray-tracing pipeline architecture and the rasterization-like discretization, will be introduced in order to allow near interactive rates of computation. Common rendering pipelines in computer graphic have already been extended to ray-tracing algorithms in order to be efficiently run on the many-core architectures. We aim to adapt these architectures to the telecommunication variant of the problem. Furthermore, we will investigate rasterization approach in the context of the classical method of images as a way to exploit spatial coherence of electromagnetic propagation while offering fine-grained parallelism. The efficient implementation of the proposed algorithms on multi-core platforms and as a cloud service will enable the exploitation of precise deterministic channel characterization in the telecommunication problems where limited on-site computation resources prevent elaborate solutions. When implemented as a cloud service, the computation of radio environment will become accessible to broad range of potential users from the developers of various web and mobile applications to wireless network planers and network operators. Low-cost sensor node localization problem based on a cooperative decision making process is a perfect example of a problem that could benefit from the advanced ray-tracing techniques but cannot accommodate them on a performance-constrained hardware. In this respect we will investigate the possibilities of enhancing the accuracy and robustness of the location estimation by integration of the precise deterministic channel model, implemented as a cloud service, into the localization procedures. In particular, pattern matching, also known as fingerprinting, which has the ability to reduce problems caused by the multipath late-arriving self-interfering components, is considered to be most promising.
Significance for science
The proposed project is interdisciplinary and includes a number of innovative elements, important for the development of novel technologies and, at least indirectly impacts more than just one narrow scientific field. The project will develop new knowledge in the fields of radio wave propagation, radio propagation modelling and efficient spectrum utilisation. New procedures and algorithms for improved localisation of wireless sensor nodes will be developed and new scientific knowledge acquired for more efficient management of distributed sensing infrastructure. The proposed research deals with a topic that is at the core of any wireless network planning and, as such, relevant for the wider field of telecommunications. The improved and faster radio environment characterization will have an impact on the development of communication networks that rely on high quality signal reception and spectral efficiency and will incentivise the development of the forthcoming 5G communication system. Integration of new radio environment characterization techniques with radio localization, planned for the second part of the project, will yield improvements in applications such as cargo tracking at ports and terminals, inventory management or indoor navigation solutions, just to name a few. The project partially complements and extends recently concluded basic research project J2-4197 and host research program P2-0016, focused on wireless communication networks and services. We expect original contributions to the field with publications in prominent journals and at internationally recognised conferences. Since Horizon 2020 identifies 5G, Internet of Things and Smart Cities as priority areas for research, we also expect participation in collaborative European projects. This project therefore presents an opportunity for participation also to collaborative EU projects and could stimulate the engagement of Slovenian researchers in the areas of Future Internet and 5G research.
Significance for the country
The project proposal belongs to the ICT area, which is due to it multiplicative effects recognised as one of the prioritised areas of research. Analyses show that investments in digital economy boost economic growth, employment and prosperity (http://europa.eu/rapid/press-release_IP-10-571_sl.htm). To promote the development of digital economy, EU has greatly expanded its investments in the development of 5G technologies and promotes investment in the field of smart connectivity. The project proposal directly responds to the mentioned R&D challenges. The results of the project will be directly applicable to several areas, such as traffic, logistics, creative industries as well as in the field of public infrastructure management and provision of public services. The results will have a direct positive impact to (1) further development of new location-dependent and highly personalised and contextualised services and (2) the maximisation of radio spectrum utilisation. The project will therefore foster development of new marketable location based services as well as promote utilisation of integrated public services. New methods will be implemented and demonstrated on the LOG-a-TEC experimental sensor testbed, so they can be further used in support to different public services and therefore as a pilot platform for deployment of innovative Smart Cities solutions. According to Juniper research (http://www.juniperresearch.com/press-release/context-and-location-based-services-pr2), location based service market is to exceed 43 bn USD by 2019, so we believe that the investment in the development of enhanced localisation techniques is also economically justified.   As indicated in previous paragraphs, research results will be interesting for SMEs and start-ups, telecommunications operators as well as public network operators and managers of public infrastructure. Since the project is directed towards the digital sector, which has a very young workforce (http://europa.eu/rapid/press-release_MEMO-13-779_sl.htm), the project will also have a positive impact on tackling the problem of youth unemployment, the latter being one of the biggest challenges of European Union. The collaboration of Alanta and Xlab as consortium partners presents additional assurance that special attention will be given to successful commercialisation of research results. Particularly so since Xlab is one of the most successful Slovenian companies in the field of development and commercialization of web and mobile applications in the cloud while Alanta is profiling itself as a specialised company that offers specific services in the field of cloud infrastructure. Both companies are entering the project aiming for solution of their clearly established business needs. This means that the outcomes of this project have a great chance of commercialisation and also that the existing products and services of both companies obtain a greater chance for commercialisation through this project.
Most important scientific results Interim report, final report
Most important socioeconomically and culturally relevant results Interim report, final report
Views history
Favourite