XR Capacity Enhancement through Multi-Connected XR Tethering Groups
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866915673232375808 |
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| author | Ahsen, Muhammad Yanakiev, Boyan Rosa, Claudio Adeogun, Ramoni |
| author_facet | Ahsen, Muhammad Yanakiev, Boyan Rosa, Claudio Adeogun, Ramoni |
| contents | Extended Reality (XR) applications have limited capacity in 5th generation-advanced (5G-A) cellular networks due to high throughput requirements coupled with strict latency and high reliability constraints. To enhance XR capacity in the downlink (DL), this paper investigates multi-connected XR tethering groups (TGrs), comprising an XR device and a cooperating 5G-A device. This paper presents investigations for two types of cooperation within XR TGr, i.e., selection combining (SC) and soft combining and their impact on the XR capacity of the network. These investigations consider joint hybrid automatic repeat request (HARQ) feedback processing algorithm and also propose enhanced joint Outer Loop Link Adaptation (OLLA) algorithm to leverage the benefits of multi-connectivity. These enhancements aim to improve the spectral efficiency of the network by limiting HARQ retransmissions and enabling the use of higher modulation and coding scheme (MCS) indices for given signal-to-interference-plus-noise ratio (SINR), all while maintaining or operating below than the target block error rate (BLER). Dynamic system-level simulation demonstrate that XR TGrs with soft combining achieve performance improvements of 23 - 42% in XR capacity with only XR users and 38-173% in the coexistence scenarios consisting of XR users and enhanced mobile broadband (eMBB) user. Furthermore, the enhanced joint OLLA algorithm enables similar performance gains even when only one device per XR TGr provides channel state information (CSI) reports, compared to scenarios where both devices report CSI. Notably, XR TGrs with soft combining also enhance eMBB throughput in coexistence scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_12368 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | XR Capacity Enhancement through Multi-Connected XR Tethering Groups Ahsen, Muhammad Yanakiev, Boyan Rosa, Claudio Adeogun, Ramoni Signal Processing Extended Reality (XR) applications have limited capacity in 5th generation-advanced (5G-A) cellular networks due to high throughput requirements coupled with strict latency and high reliability constraints. To enhance XR capacity in the downlink (DL), this paper investigates multi-connected XR tethering groups (TGrs), comprising an XR device and a cooperating 5G-A device. This paper presents investigations for two types of cooperation within XR TGr, i.e., selection combining (SC) and soft combining and their impact on the XR capacity of the network. These investigations consider joint hybrid automatic repeat request (HARQ) feedback processing algorithm and also propose enhanced joint Outer Loop Link Adaptation (OLLA) algorithm to leverage the benefits of multi-connectivity. These enhancements aim to improve the spectral efficiency of the network by limiting HARQ retransmissions and enabling the use of higher modulation and coding scheme (MCS) indices for given signal-to-interference-plus-noise ratio (SINR), all while maintaining or operating below than the target block error rate (BLER). Dynamic system-level simulation demonstrate that XR TGrs with soft combining achieve performance improvements of 23 - 42% in XR capacity with only XR users and 38-173% in the coexistence scenarios consisting of XR users and enhanced mobile broadband (eMBB) user. Furthermore, the enhanced joint OLLA algorithm enables similar performance gains even when only one device per XR TGr provides channel state information (CSI) reports, compared to scenarios where both devices report CSI. Notably, XR TGrs with soft combining also enhance eMBB throughput in coexistence scenarios. |
| title | XR Capacity Enhancement through Multi-Connected XR Tethering Groups |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2512.12368 |