POLAR: Passive object localization with IEEE 802.11ad using phased antenna arrays

García, Daniel Hernández; Lacruz, Jesus O.; Mateo, Pablo Jiménez; Widmer, Joerg

doi:10.1109/infocom41043.2020.9155383

Cited by 19 publications

(14 citation statements)

References 20 publications

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“…[125]- [127], [132], [134]- [136], [141], [142], [153]-[155] 2) In AP-centric algorithm, the intelligence resides in a computing entity connected to one or multiple APs, which coalesce their measurements from multiple clients in order to estimate the location of each client. These schemes are ideal for seamless network management purposes (e.g., to optimize client-AP associations) but scale less than client-centric approaches when the number of clients increases.…”

Section: Clientcentric Ap-centric Ap-client Cooperationmentioning

confidence: 99%

A Review of Millimeter Wave Device-Based Localization and Device-Free Sensing Technologies and Applications

Shastri

Valecha

Bashirov

et al. 2022

IEEE Commun. Surv. Tutorials

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The commercial availability of low-cost millimeterwave (mmWave) communication and radar devices is starting to improve the adoption of such technologies in consumer markets, paving the way for large-scale and dense deployments in fifthgeneration (5G)-and-beyond as well as 6G networks. At the same time, pervasive mmWave access will enable device localization and device-free sensing with unprecedented accuracy, especially with respect to sub-6 GHz commercial-grade devices.This paper surveys the state of the art in device-based localization and device-free sensing using mmWave communication and radar devices, with a focus on indoor deployments. We overview key concepts about mmWave signal propagation and system design, detailing approaches, algorithms and applications for mmWave localization and sensing. Several dimensions are considered, including the main objectives, techniques, and performance of each work, whether they reached an implementation stage, and which hardware platforms or software tools were used.We analyze theoretical (including signal processing and machine learning), technological, and implementation (hardware and prototyping) aspects, exposing under-performing or missing techniques and items towards enabling a highly effective sensing of human parameters, such as position, movement, activity and vital signs. Among many interesting findings, we observe that device-based localization systems would greatly benefit from commercial-grade hardware that exposes channel state information, as well as from a better integration between standardcompliant mmWave initial access and localization algorithms, especially with multiple access points (APs). Moreover, more advanced algorithms requiring zero-initial knowledge of the environment would greatly help improve the adoption of mmWave simultaneous localization and mapping (SLAM). Machine learning (ML)-based algorithms are gaining momentum, but still require the collection of extensive training datasets, and do not yet generalize to any indoor environment, limiting their applicability. Manuscript received xxxx xx, xxxx . . .

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Section: Clientcentric Ap-centric Ap-client Cooperationmentioning

confidence: 99%

A Review of Millimeter Wave Device-Based Localization and Device-Free Sensing Technologies and Applications

Shastri

Valecha

Bashirov

et al. 2022

IEEE Commun. Surv. Tutorials

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“…We would like to highlight that MultiLoc is the first system implemented on COTS devices that enables estimation of AoA and ToF. Finally, also passive mmWave localization was investigated in [8,45,46].…”

Section: Related Workmentioning

confidence: 99%

“…The large number of elements in directional mmWave phased antenna arrays enables very accurate estimation of the angle of the signal and the high temporal resolution from the multi-GHz bandwidth provides excellent ranging accuracy. These characteristics make mmWave technology an ideal candidate to design highly accurate wireless location systems [8,30,47]. A location system estimates the Angle of Arrival (AoA) and Time of Flight (ToF) of the path between an Access Point (AP) and a client to determine the position of the client.…”

Section: Introductionmentioning

confidence: 99%

Augmenting mmWave localization accuracy through sub-6 GHz on off-the-shelf devices

Blanco

Mateo

Gringoli

et al. 2022

Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services

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Millimeter-wave (mmWave) technology is an important element to increase the throughput and reduce latency of future wireless networks. At the same time, its high bandwidth and highly directional antennas allow for unprecedented accuracy in wireless sensing and localization applications. In this paper, we thoroughly analyze mmWave localization and find that it is either extremely accurate or has a very high error, since there is significant mmWave coverage via reflections and even through walls. As a consequence, sub-6 GHz technology can not only provide (coarse) localization where mmWave is not available, but is also critical to decide among multiple candidate antennas and APs for accurate mmWave localization.Based on these insights, we design a high-accuracy joint mmWave and sub-6 GHz location system. We enable CSI-based angle estimation and FTM-based ranging on off-the-shelf mmWave devices to implement our mechanism and carry out an extensive measurement campaign. Our system is the first to achieve 18 cm median location error with off-the-shelf devices under their normal mode of operation. We further release the location system (and in particular the CSI and FTM functionality) as well as the trace data from the measurement campaign to the research community. CCS CONCEPTS• Networks → Location based services.

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“…. , L − 1, using standard techniques [21], see also Section III. Path is mapped onto the corresponding reflector distance using d = cτ /4B, where B and c respectively represent the transmitted signal bandwidth and the speed of light.…”

Section: B Cir Modelmentioning

confidence: 99%

RAPID: Retrofitting IEEE 802.11ay Access Points for Indoor Human Detection and Sensing

Pegoraro¹,

Lacruz²,

Meneghello³

et al. 2021

Preprint

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In this work we present RAPID, a Joint Communication & Radar (JCR) system based on next generation IEEE 802.11ay WiFi networks in the 60 GHz band, which retrofits existing communication hardware to perform zerocost monitoring of human movement and activities in indoor spaces. Most of the available approaches for human sensing at millimeter-waves employ special-purpose radar devices, which are utilized to retrieve and analyze the small-scale Doppler effect (micro-Doppler) caused by human motion. This is key to achieve fine-grained sensing applications such as simultaneous activity recognition and person identification. We show that IEEE 802.11ay Access Points (APs) can be retrofitted to perform radar-like extraction of micro-Doppler effects of multiple human subjects. While radar systems entail the deployment of additional hardware, our framework performs activity recognition and person identification using IEEE 802.11ay wireless networks with no modifications to the transmitted packet structure specified by the standard. We leverage the in-packet beam training capability of IEEE 802.11ay to accurately localize and track multiple individuals using the estimated Channel Impulse Response (CIR), while the beam tracking mechanism embedded in data packets allows to extract the desired micro-Doppler (µD) signatures of the subjects. We implement our system on an IEEE 802.11aycompatible full-duplex FPGA platform with phased antenna arrays, which can estimate the CIR from the reflections of transmitted packets. Using two access points, we achieve reliable positioning and tracking of multiple subjects, and an accuracy of 93% and 90% for activity recognition and person identification, respectively.

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POLAR: Passive object localization with IEEE 802.11ad using phased antenna arrays

Cited by 19 publications

References 20 publications

A Review of Millimeter Wave Device-Based Localization and Device-Free Sensing Technologies and Applications

A Review of Millimeter Wave Device-Based Localization and Device-Free Sensing Technologies and Applications

Augmenting mmWave localization accuracy through sub-6 GHz on off-the-shelf devices

RAPID: Retrofitting IEEE 802.11ay Access Points for Indoor Human Detection and Sensing

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