University of Oulu

S. Samarakoon, M. Bennis, W. Saad and M. Debbah, "Federated Learning for Ultra-Reliable Low-Latency V2V Communications," 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates, 2018, pp. 1-7. doi: 10.1109/GLOCOM.2018.8647927

Federated learning for ultra-reliable low-latency V2V communications

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Author: Samarakoon, Sumudu1; Bennis, Mehdi1; Saad, Walid2;
Organizations: 1Centre for Wireless Communications, University of Oulu, Oulu, Finland
2Bradly Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA USA
3Huawei Tehnologies, Paris Research Center, France
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2019-09-18


In this paper, a novel joint transmit power and resource allocation approach for enabling ultra-reliable low-latency communication (URLLC) in vehicular networks is proposed. The objective is to minimize the network-wide power consumption of vehicular users (VUEs) while ensuring high reliability in terms of probabilistic queuing delays. In particular, a reliability measure is defined to characterize extreme events (i.e., when vehicles’ queue lengths exceed a predefined threshold with non-negligible probability) using extreme value theory (EVT). Leveraging principles from federated learning (FL), the distribution of these extreme events corresponding to the tail distribution of queues is estimated by VUEs in a decentralized manner. Finally, Lyapunov optimization is used to find the joint transmit power and resource allocation policies for each VUE in a distributed manner. The proposed solution is validated via extensive simulations using a Manhattan mobility model. It is shown that FL enables the proposed distributed method to estimate the tail distribution of queues with an accuracy that is very close to a centralized solution with up to 79% reductions in the amount of data that need to be exchanged. Furthermore, the proposed method yields up to 60% reductions of VUEs with large queue lengths, without an additional power consumption, compared to an average queue-based baseline. Compared to systems with fixed power consumption and focusing on queue stability while minimizing average power consumption, the reductions in extreme events of the proposed method is about two orders of magnitude.

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Series: IEEE Global Communications Conference
ISSN: 2334-0983
ISSN-E: 2576-6813
ISSN-L: 2334-0983
ISBN: 978-1-5386-4727-1 978-1-5386-6976-1
ISBN Print: 978-1-5386-4728-8
Article number: 8647927
DOI: 10.1109/GLOCOM.2018.8647927
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
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