Path Assignment in Mesh Networks at the Edge of Wireless Networks
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910901236400128 |
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| author | Kumar, Siddhartha Moghaddam, Mohammad Hossein Wolfgang, Andreas Svensson, Tommy |
| author_facet | Kumar, Siddhartha Moghaddam, Mohammad Hossein Wolfgang, Andreas Svensson, Tommy |
| contents | We consider a mesh network at the edge of a wireless network that connects users to the core network via multiple base stations. For this scenario, we present a novel tree-search-based algorithm that strives to identify effective communication path to the core network for each user by maximizing the signal-to-noise-plus-interference ratio (SNIR) along the chosen path. We show that, for three mesh networks of varying sizes, our algorithm selects paths with minimum SNIR values that are 3 dB to 18 dB higher than those obtained through an algorithm that disregards interference within the network, 16 dB to 20 dB higher than those chosen randomly by a random path selection algorithm, and 0.5 dB to 7 dB higher compared to a recently introduced genetic algorithm (GA). Furthermore, we demonstrate that our algorithm has lower computational complexity compared to the GA in networks where its performance is within 2 dB of ours. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_10228 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Path Assignment in Mesh Networks at the Edge of Wireless Networks Kumar, Siddhartha Moghaddam, Mohammad Hossein Wolfgang, Andreas Svensson, Tommy Networking and Internet Architecture Information Theory We consider a mesh network at the edge of a wireless network that connects users to the core network via multiple base stations. For this scenario, we present a novel tree-search-based algorithm that strives to identify effective communication path to the core network for each user by maximizing the signal-to-noise-plus-interference ratio (SNIR) along the chosen path. We show that, for three mesh networks of varying sizes, our algorithm selects paths with minimum SNIR values that are 3 dB to 18 dB higher than those obtained through an algorithm that disregards interference within the network, 16 dB to 20 dB higher than those chosen randomly by a random path selection algorithm, and 0.5 dB to 7 dB higher compared to a recently introduced genetic algorithm (GA). Furthermore, we demonstrate that our algorithm has lower computational complexity compared to the GA in networks where its performance is within 2 dB of ours. |
| title | Path Assignment in Mesh Networks at the Edge of Wireless Networks |
| topic | Networking and Internet Architecture Information Theory |
| url | https://arxiv.org/abs/2411.10228 |