@inproceedings{f8527cfe80294126a7650539f17a4969,
title = "Representation Learning with Attention for Spatial Reuse Optimization in Dense WLANs",
abstract = "IEEE802.11ax is designed to support self-configuration and adaptation functionality in dense deployment to enhance dynamic network conditions. Presence of variable transmission range is one of the major bottlenecks to network performance. In the absence of proper power management, co-existing IEEE 802.11ax access points cause co-channel interference, degrading throughput. Therefore, it is essential to consider the impact of the variable transmit power of neighboring nodes to optimize the network performance. This work proposes an affinityGNN-attention mechanism to capture neighborhood transmit power to generate an expressive network representation. Experiments results show that the attention module integration improves the prediction accuracy and robustness of the baseline affinityGNN model.",
keywords = "Coexistence interference, IEEE802.11, Network management",
author = "Stephen Azeez and Shagufta Henna",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 8th International Congress on Information and Communication Technology, ICICT 2023 ; Conference date: 20-02-2023 Through 23-02-2023",
year = "2023",
doi = "10.1007/978-981-99-3091-3_77",
language = "English",
isbn = "9789819930906",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "949--959",
editor = "Xin-She Yang and Sherratt, {R. Simon} and Nilanjan Dey and Amit Joshi",
booktitle = "Proceedings of 8th International Congress on Information and Communication Technology - ICICT 2023",
}