Comparative Analysis of Sub-band Allocation Algorithms in In-body Sub-networks Supporting XR Applications
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929281396899840 |
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| author | Bagherinejad, Saeed Jacobsen, Thomas Pratas, Nuno K. Adeogun, Ramoni O. |
| author_facet | Bagherinejad, Saeed Jacobsen, Thomas Pratas, Nuno K. Adeogun, Ramoni O. |
| contents | In-body subnetworks (IBS) are envisioned to support reliable wireless connectivity for emerging applications including extended reality (XR) in the human body. As the deployment of in-body sub-networks is uncontrollable by nature, the dynamic radio resource allocation scheme in place becomes of the uttermost importance for the performance of the in-body sub-networks. This paper provides a comparative study on the performance of the state-of-the-art interference-aware sub-band allocation algorithms in in-body sub-networks supporting the XR applications. The study identified suitable models for characterizing in-body sub-networks which are used in a snapshot-based simulation framework to perform a comprehensive evaluation of the performance of state-of-art sub-band allocation algorithms, including greedy selection, sequential greedy selection (SG), centralized graph coloring (CGC), and sequential iterative sub-band allocation (SISA). The study shows that for XR requirements, the SISA and SG algorithms can support IBS densities up to 75% higher than CGC. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_11891 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Comparative Analysis of Sub-band Allocation Algorithms in In-body Sub-networks Supporting XR Applications Bagherinejad, Saeed Jacobsen, Thomas Pratas, Nuno K. Adeogun, Ramoni O. Information Theory Signal Processing In-body subnetworks (IBS) are envisioned to support reliable wireless connectivity for emerging applications including extended reality (XR) in the human body. As the deployment of in-body sub-networks is uncontrollable by nature, the dynamic radio resource allocation scheme in place becomes of the uttermost importance for the performance of the in-body sub-networks. This paper provides a comparative study on the performance of the state-of-the-art interference-aware sub-band allocation algorithms in in-body sub-networks supporting the XR applications. The study identified suitable models for characterizing in-body sub-networks which are used in a snapshot-based simulation framework to perform a comprehensive evaluation of the performance of state-of-art sub-band allocation algorithms, including greedy selection, sequential greedy selection (SG), centralized graph coloring (CGC), and sequential iterative sub-band allocation (SISA). The study shows that for XR requirements, the SISA and SG algorithms can support IBS densities up to 75% higher than CGC. |
| title | Comparative Analysis of Sub-band Allocation Algorithms in In-body Sub-networks Supporting XR Applications |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2403.11891 |