Concurrent transmissions (CTX) are a state-of-the-art technique for low-power wireless networking, enabling performance unmatched by conventional routing-based approaches. However, their use is notoriously complex, as it hinges on many low-level system aspects distracting developers from the protocol logic. This is exacerbated in ultra-wideband (UWB) radios, recently shown to enable higher CTX performance than IEEE 802.15.4 and BLE, but significantly more energy-hungry, posing new problems to developers. A case in point is the deep sleep mode in popular UWB radios: it yields negligible consumption (50 nA) in periods of inactivity—crucial in real-world deployments—during which, however, clock drifts may disrupt the tight time synchronization required by CTX. Existing systems avoid the complexity of reconciling these conflicting needs via solutions with significantly higher consumption, hampering real-world applicability. We address these challenges with SAMU, a novel framework allowing developers to fully exploit the advantages of CTX over UWB via simple, expressive, and flexible abstractions removing the underlying complexity, embodied in an optimized and efficient runtime support. A distinctive trait of SAMU is the fine-grained control it provides over individual CTX, unlocking design opportunities unavailable in existing frameworks offering only high-level building blocks (e.g., CTX-based floods). We illustrate the power of SAMU by showing how existing CTX protocols can be easily built atop it, and evaluate the resulting performance in a large-scale testbed. Our results confirm that SAMU successfully combines high-level programming with a low-latency, energy-efficient, and reliable runtime support, providing a foundation for the protocol design and real-world deployment of CTX-based systems.

The synergy between the accurate trajectories offered by ultra-wideband (UWB) systems and techniques to extract higher-level mobility patterns is largely unexplored. We study whether staple techniques designed for systems with coarser resolution apply to UWB, investigating quantitatively the quality of the fine-grained analyses enabled by the latter. To this end, we contribute a novel family of metrics suited to the high UWB spatio-temporal resolution and use them to configure and ascertain the quality of representative techniques along several dimensions. We focus on the well-known stop-move pattern and derive our findings from a real museum setting with the use case of capturing visits to exhibits. We acquire UWB trajectories in both controlled ( in vitro ) and uncontrolled ( in vivo ) conditions, along with ground truth. Despite exhibits being very close to each other, our results show that stops near them can be correctly identified and associated in the vast majority of cases and with very small spatio-temporal error. These positive results from real-world experiments, along with our technical contributions, open new opportunities in exploiting UWB for mobility analyses.

Real-time monitoring of visitor behavior in venues such as museums and shops offers valuable insights into visitor preferences, hotspots, and space occupancy. Visitors typically demonstrate interest, by stopping near points of interest (POIs), such as museum exhibits, for brief durations, often on the order of a few seconds, posing challenges for localization technology and stop detection. In this paper, we present StopTracker, a framework supporting the stop-move segmentation of indoor trajectory streams, relying on Ultra-wideband (UWB) localization for the accurate monitoring of visitor stops and preferences. StopTracker is constructed using SPDstreams, an advanced variant of the popular stop-detection technique SPD, and designed to handle evolving stops. Additionally, StopTracker support the dynamic ranking of POIs. By leveraging UWB technology, StopTracker aims to provide accurate and actionable insights into visitor behavior, enhancing both visitor experience and space management.

In many low-power wireless systems, a condition occurring at some nodes (e.g., an anomalous sensor sample, an aperiodic packet to transmit, a new joining node) determines whether the entire network should be awake (e.g., to react to the anomaly, deliver the packet, update the node group) or enter sleep. State-of-the-art protocols exploit periodic network-wide floods based on concurrent transmissions (e.g., via Glossy) to establish the global decision quickly, reliably, and efficiently. Still, time is of the essence: the faster the network agrees, the faster it either reacts or enters sleep.

Applications of ultra-wideband (UWB) for distance estimation (ranging) and localization often involve users wearing tags. Unfortunately, the human body causes significant signal attenuation, reducing ranging accuracy. This specific case of non-line-of-sight (NLOS) condition has received little attention in the literature. Further, state-of-the-art techniques tackling generic NLOS are often based on machine learning, limiting their exploitation on embedded devices. We pursue an alternative approach and show that the features offered by the UWB transceiver, largely neglected by the literature, can be directly exploited to reliably detect human occlusions and optimize ranging accordingly. We base our findings on an extensive exper-imental campaign exploring many radio, system, and deployment dimensions in two environments, resulting in practical guidelines immediately available to the designers of UWB-based systems.

Ultra-wideband (UWB) localization enables user tracking with high spatio-temporal resolution, whose exploitation for detecting higher-level mobility patterns is largely unexplored. We study whether i) existing detection techniques, developed for coarser-grained localization, apply also to UWB trajectories, and ii) the quantitative extent to which this enables finer-grained analyses. We focus on the well-known stop-move pattern, and offer a concrete use case of capturing visits in a real museum. We contribute a novel metric suited to the high UWB spatio-temporal resolution and use it to evaluate representative techniques. We deploy a UWB system in a 25×15 m2museum area and base our analysis on 70000+ positions and 200+ ground-truth stops. These are very close in space and time, yet results confirm very accurate spatio-temporal estimation in the vast majority of cases.

Research advances in low-power wireless systems have greatly benefited from the availability of public testbeds. However, none is currently available for the increasingly popular ultra-wideband (UWB) radios enabling communication and localization. We present Cloves, the first public large-scale testbed supporting UWB.

Concurrent transmissions (CTX) enable low latency, high reliability, and energy efficiency. Nevertheless, existing protocols typically exploit CTX via the Glossy system, whose fixed-length network-wide floods are entirely dedicated to disseminating a single packet.

Time difference of arrival (TDoA) localization with ultra-wideband (UWB) radios is rapidly gaining interest. Nevertheless, TDoA requires tightly time-synchronized anchors, either via wireless synchronization in small-scale setups with all anchors in range or via expensive wired backbones, both ultimately hampering the use of TDoA in large-scale areas. In this paper we present TALLA, a novel wireless-only TDoA approach able to scale over large operational areas without sacrificing positioning accuracy. TALLA relies on a TDMA schedule enabling continuous, multi-hop operation of the anchor infrastructure. We evaluate TALLA in our 12-node UWB testbed and in much larger (>100 anchors) simulated areas, empowered by a technique that generates synthetic timing information faithfully reproducing the trends of the real one. Our real and simulated results show that TALLA achieves decimeter-level accuracy while tracking a moving target across several hops.

Concurrent transmissions can be used to enhance network reliability and scalability and to reduce energy consumption and latency. This paper studies their applicability for communication and ranging in UWB networks, where they are hitherto largely unexplored. To this end, we follow an experiment-driven approach and show that i) different pulse repetition frequencies virtually double the number of non-interfering channels, ii) concurrent transmissions with different preamble codes are unreliable, unless transmitters are tightly synchronized, and iii) under the same RF configuration, UWB radios are very likely to receive one of the packets transmitted concurrently by multiple senders, unlocking opportunities similar to those exploited in low-power narrowband radios. We argue that our findings can inform the design of novel communication and ranging protocols exploiting the unique advantages of concurrent transmissions, potentially inspiring a new wave of research on UWB radios.