XR streaming performance with wi-fi 7 multi-link operation

Jonsson, Anders; Carrascosa Zamacois, Marc; Galati Giordano, Lorenzo; Wilhelmi Roca, Francesc; Fontanesi, Gianluca; Geraci, Giovanni; Bellalta, Boris

doi:http://dx.doi.org/10.1109/OJCOMS.2025.3594950

XR streaming performance with wi-fi 7 multi-link operation

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Citation

Carrascosa-Zamacois M, Galati-Giordano L, Wilhelmi F, Fontanesi G, Jonsson A, Geraci G, et al. XR streaming performance with wi-fi 7 multi-link operation. IEEE Open J Commun Soc. 2025 Aug 1;6:6477-90. DOI: 10.1109/OJCOMS.2025.3594950

Abstract

Extended Reality (XR) has stringent throughput and delay requirements that are hard to meet with current wireless technologies. Missing these requirements can lead to worsened picture quality, perceived lag between user input and corresponding output, and even dizziness for the end user. In this paper, we study the capability of Wi-Fi 7, and its novel support for Multi-Link Operation (MLO), to cope with these tight requirements. Our study is based on simulation results extracted from an MLO-compliant simulator that realistically reproduces VR traffic. Results show that MLO can sustain Virtual Reality (VR) applications. By jointly using multiple links with independent channel access procedures, MLO can reduce the overall delay, which is especially useful in the uplink, as it has more stringent requirements than the downlink, and is instrumental in delivering the expected performance. We show that using MLO can support more users per Access Point (AP) than an equivalent number of links using Single Link Operation (SLO). We also show that, while maintaining the same overall bandwidth, a higher number of MLO links with narrower channels leads to lower delays than a lower number of links with wider channels. We also study the impact of Overlapping Basic Service Sets (OBSS) on performance of XR applications, showing how SLO struggles to maintain a low delay when OBSS activity increases, and how MLO can cope with this interference by using MLO-aware channel assignment strategies. Finally, we consider random positioning for the users, showcasing that MLO can support 5× more users than SLO.