Periodic Reporting for period 2 - eWINE (elastic WIreless Networking Experimentation)
Reporting period: 2017-01-01 to 2018-04-30
eWINE will have a major social impact for society through its development of the next generation wireless products and applications for a broad range of applications domains, from public safety to the home environment by the development and ad hoc deployment of networks with smart and dynamic configuration capabilities that support public safety at large ad hoc events, such as sports events, city events and world congresses. In regards to the environment, eWINE's impact is as follows: much higher efficiency in terms of energy consumption and electromagnetic exposure, further optimizations and intelligent configuations through the introduction of planning and learning strategies into the cognitive loop and reduction of energy consumption while increasing comfort in the home environment through intelligent and flexible control systems.
The overall objectives are to enable on demand end to end basic wireless connectivity capable of delivering (i) elastic connectivity services from an Over-The-Top (OTT) service provider to fixed and mobile wireless devices within dense network scenarios, (ii) enable elastic resource sharing in dense deployments of heterogeneous and small cell networks (HetSNets) in a dynamic way to provide Quality of Service to the many wireless services running on the wireless devices, (iii) develop and evaluate an open and reconfigurable physical layer that is able to intelligently adapt radio parameters to the current network and application context and (iv) lastly, educate the research community, industrial professionals as well as the general public to increase awareness of problems that occur in dense and dynamic wireless networks and possible solutions to these, thus promoting the uptake of the project results by providing an Intelligence Toolbox (i.e. an open source repository of the software components developed in the project and tested in the showcases).
In the area of Intelligent Algorithm Design, Development, Implementation, partners worked on the creation of the demonstrator about SUMO optimization for the wireless audio conferencing scenario and the creation of prediction algorithms and datasets for the intelligence repository for Showcase 2; worked on the optimization algorithm design on power-aware mode selection between D2D communication mode and infrastructure mode in LTE networks and the implementation of the D2D Physical channels with compliance to 3GPP LTE standard in Software-defined-radio testbed, tested and prepared the demonstrator for Showcase 1, worked on the Flexible FPGA PHY layer implementation (GFDM), waveform parameter optimization, and efficient beam-alignment algorithm for mmWave links which were included in Showcase 3, contributed to the early work on channel selection as a component for Showcase 2, worked on the Manycore optimizations of the OFDM modem (WiFi-like waveform) Tx. Multithreading, Thread Pool and timing performance measurements (profiling) to show the results for Showcase 3.
The socio-economic impact and wider implications are seen by producing a far more efficient operation in dense heterogeneous environments with a energy efficiency which positively impacts the environment, costs which can be further reduced when utilizing WiFi D2D, increased capacity and improved battery consumption in end-user terminals, a simplified integration of applications with services that can provide location information which reduces the costs and efforts of enabling location-awareness in wireless networks, QoS improvement and more energy efficient devices and electrical power consumption, reduction of the installation complexity, increase in the global network capacity, and improving search and rescue capabilities.