Design and implementation of renewably-powered based stations with heterogeneous access channels
Contact names: Dr. Stephan Weiss
Institution: University of Strathclyde
Application deadline:
Description: The optimisation of heterogeneous access networks, where users can be connected to a rural base station via several channels (e.g., 5.2GHz WiFi & UHF TVWS, or possibly different TVWS channels with different channel characteristics). The aim will be to develop Bayesian belief propagation algorithms that have a sufficiently low complexity to address mobile systems with a higher number of users. The ESR will also drive FPGA
implementations for radio devices, creating “minimal” LTE radios that satisfy the specifications, but through a reduced number of building blocks so as to attain low power consumption. The ESR will be in charge of leading the activities on modelling BS power consumption, harvesters and storage systems for BSs (see WP2). Measurements from real deployments (wind and solar powered base stations across the west coast of Scotland, Bute & Tiree, and solar powered BSs in Kenya) will also be available.
Expected Results: Definition of planning tools for station assignment that are informed by realistic measurements/statistics about renewable energy availability, and be able to construct lower power radio devices that can operate in, e.g., rural environments.
Mobility Schedule: The candidate will be mainly at University of Strathclyde. After 24 months, the ESR will join Toshiba Research Laboratories for 9 months to preliminarily validate the proposed heterogeneous access channel algorithms under the supervision of Dr. Filippo Tosato.
Requirements of the candidate:
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At the time of recruitment, the applicant must not have lived in UK for more than 12 months in the previous 36 months
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A Master degree in Telecommunications, Computer Science or equivalent
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Once selected by the SCAVENGE consortium for the ESR positions, the applicants must apply for PhD studentship at University of Strathclyde.
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Knowledge on mobile networks, sensor networks, big data
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Knowledge on energy systems and management
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Ability and motivation to conduct high-quality research, including publishing the results in relevant venues
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Strong programming skills (e.g. C/C++, Java, Python).
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Working experience in the areas of Mobile Networks, Sensor Networks, Smart Grid, Energy Harvesting, Big Data management, Cloud computing is an advantage.
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Knowledge on Optimization Theory is an advantage.
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Very good communication skills in oral and written English.
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Open-mindedness, strong integration skills and team spirit.