P
Paul Patras
Researcher at University of Edinburgh
Publications - 74
Citations - 2507
Paul Patras is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Wireless network & Throughput. The author has an hindex of 18, co-authored 66 publications receiving 1545 citations. Previous affiliations of Paul Patras include Maynooth University & Charles III University of Madrid.
Papers
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Journal ArticleDOI
Deep Learning in Mobile and Wireless Networking: A Survey
TL;DR: This paper bridges the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas, and provides an encyclopedic review of mobile and Wireless networking research based on deep learning, which is categorize by different domains.
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Deep Learning in Mobile and Wireless Networking: A Survey
TL;DR: In this article, the authors provide an encyclopedic review of mobile and wireless networking research based on deep learning, which they categorize by different domains and discuss how to tailor deep learning to mobile environments.
Proceedings ArticleDOI
Long-Term Mobile Traffic Forecasting Using Deep Spatio-Temporal Neural Networks
Chaoyun Zhang,Paul Patras +1 more
TL;DR: In this article, a Spatio-Temporal Neural Network (STN) architecture was proposed for precise network-wide mobile traffic forecasting, and a Double STN technique was introduced to combine the STN predictions with historical statistics, thereby making faithful longterm mobile traffic projections.
Journal ArticleDOI
Optimal Configuration of 802.11e EDCA for Real-Time and Data Traffic
TL;DR: This paper proposes a novel algorithm for EDCA that, given the throughput and delay requirements of the stations that are present in the WLAN, computes the optimal configuration of the EDCA parameters.
Journal ArticleDOI
Greening wireless communications: Status and future directions
TL;DR: A survey of the recent proposals for green wireless communications, with a view to understanding the most relevant sources of inefficient energy consumption and how these are tackled by current solutions, and introduces a classification of the existing mechanisms based on their operational time-scale.