The growing proliferation of Wi-Fi 6E devices, which operate at a high transmission power in the same frequency band used by ultra-wideband (UWB) technology, poses significant challenges to the reliability of UWB-based systems. Prior work has explored the impact of Wi-Fi 6E traffic on UWB performance experimentally using real-world testbeds, but lacks a theoretical framework capturing how Wi-Fi 6E’s physical-layer (PHY) settings, signal strength, and traffic profile affect UWB performance. We address this gap by introducing a probabilistic error model that accurately estimates the packet error rate (PER) of UWB systems operating alongside Wi-Fi 6E traffic. Using a conducted test setup, we analyze coexisting transmissions to characterize real-world Wi-Fi 6E traffic (e.g., airtime, inter-arrival times, and channel occupancy) and quantify the sensitivity of UWB transmissions to Wi-Fi 6E interference for different PHY settings, traffic profiles, and signal strengths. We leverage this characterization to parametrize the model using different approaches, ranging from a trace-based estimation of the collision probability to an analytical derivation of Wi-Fi 6E’s channel occupancy. This allows us to explore different trade-offs w.r.t. the model’s accuracy and generality. Our experimental evaluation demonstrates that our model accurately captures the UWB PER, with average deviations as low as 3.6% on conducted measurements and below 9.7% on real-world experiments in a university building.

Ultra-wideband (UWB) devices operate only on a few frequency channels and commonly lack clear channel assessment capabilities: this makes it difficult to support several devices operating concurrently within a single network or to avoid coexistence issues with other UWB-based systems operating in close proximity. To address this issue, the IEEE 802.15.4 standard proposes the use of complex channels (i.e., diverse combinations of frequency channels and preamble codes) to enable multiple orthogonal transmissions. However, existing studies have shown that concurrent UWB transmissions on different complex channels are unreliable and incur high packet loss. In this paper, we investigate and shed light on the reason for this packet loss. We then present concrete methods to boost the reliability of concurrent UWB communications over different complex channels and demonstrate their effectiveness experimentally. In detail, we show that the synchronization and clock frequency offset among concurrent transmitters as well as the employed physical layer settings can be used to increase communication performance over different complex channels. Our study shows the feasibility of more than eight concurrent UWB transmissions on the same frequencies, sustaining a packet reception rate above 99% while retaining the ability to carry out centimetre-accurate ranging.

The introduction of the Wi-Fi 6E standard operating in the 6 GHz frequency band is a serious threat for IoT systems based on ultra-wideband technology, as they share portions of the same spectrum. Wi-Fi 6E devices can in fact support channel bandwidths up to 160 MHz and operate at a much higher transmission power compared to ultra-wideband devices, which may lead to severe coexitence issues and degraded performance. However, whether and to which extent the performance of ultra-wide band systems worsens due to Wi-Fi 6E interference has not been investigated in detail yet. In this paper, we fill this gap and study how Wi-Fi 6E traffic affects ultra-wideband performance. Our experiments on a large-scale testbed demonstrate that Wi-Fi 6E transmissions may largely disrupt ultra-wideband communications and decrease the accuracy as well as the precision of ranging measurements, with significant consequences on the efficiency of localization systems. We investigate in detail the root causes for the degraded performance and derive empirical observations that can be used to design countermeasures mitigating the impact of Wi-Fi 6E interference. These include, among others, an optimal selection of physical layer settings, as well as the use of a tight synchronization to prevent a false detection of Wi-Fi 6E traffic as ultra-wide band frames and an overshooting of the radio's automatic gain control. We further devise a technique to detect the presence of Wi-Fi 6E traffic and postpone ultra-wideband transmissions accordingly. Our experiments demonstrate that these countermeasures effectively mitigate the impact of Wi-Fi 6E interference on the performance of ultra-wide band systems.