1. Comparative Analysis of Sub-band Allocation Algorithms in In-body Sub-networks Supporting XR Applications
- Author
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Bagherinejad, Saeed, Jacobsen, Thomas, Pratas, Nuno K., and Adeogun, Ramoni O.
- Subjects
Computer Science - Information Theory ,Electrical Engineering and Systems Science - Signal Processing - Abstract
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., Comment: Accepted for IEEE WCNC 2024
- Published
- 2024