Machine type traffic scheduling with carrier aggregation for sustainable 5G dense small cell networks

Contact names: Francisco Hernandez

Institution: World Sensing

Application deadline:

Description: The project focuses on proposing novel scheduling strategies for IoT traffic over the downlink and uplink segments of a dense 5G deployment (small cells), as those foreseen for smart city applications. Carrier aggregation will be used as a tool to boost performance, even taking advantage of component carriers in unlicensed spectrum (e.g., 5 or 60 GHz, through the paradigm of Licenced Assisted Access, LAA). The option of carrier aggregation will be activated/deactivated based on the capacity/energy consumption tradeoff. Besides this, the ESR will be in charge of coordinating the energy consumption campaigns that will be carried out within WP2 to characterize the energy consumption figures of sensor nodes, as well as the corresponding battery and energy harvesting models.

Expected Results: Definition of implementable and self-organised scheduling algorithms, which satisfy throughput/latency requirements of IoT applications, while meeting the energy constraints of the small cell network

Mobility Schedule: The candidate will be mainly hosted at WorldSensing. After 20 months, the candidate will join University of Padova for a 10 month secondment to study optimization techniques to be applied to the scheduling algorithms under the supervision of Dr. Michele Rossi. The candidate will also be enrolled in the PhD program at Universidad Politecnica de Barcelona (UPC).

Requirements of the candidate:

  • At the time of recruitment, the applicant must not have lived in Spain for more than 12 months in the previous 36 months

  • A Master degree in Telecommunications, Computer Science or equivalent

  • Once selected by the SCAVENGE consortium for the ESR positions, the applicants must apply for PhD studentship at Universidad Politecnica de Catalunya (UPC).

  • Knowledge on mobile networks, sensor networks, big data

  • Knowledge on energy systems and management

  • Ability and motivation to conduct high-quality research, including publishing the results in relevant venues

  • Strong programming skills (e.g. C/C++, Java, Python).

  • Working experience in the areas of Mobile Networks, Sensor Networks, Smart Grid, Energy Harvesting, Big Data management, Cloud computing is an advantage.

  • Knowledge on Optimization Theory is an advantage.

  • Knowledge on scheduling algorithms is an advantage.

  • Very good communication skills in oral and written English.

  • Open-mindedness, strong integration skills and team spirit.