A Belief Propagation Algorithm for Multipath-Based SLAM

Leitinger, Erik; Meyer, Florian; Hlawatsch, Franz; Witrisal, Klaus; Tufvesson, Fredrik; Win, Moe Z.

doi:10.1109/twc.2019.2937781

Cited by 186 publications

(222 citation statements)

References 51 publications

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“…More important, closely-located users only a few wavelengths apart can encounter different MPCs [19]. Channel models that incorporate birthdeath processes at the level of individual MPCs are of interest to emerging applications such as MaMi communications [32], [33], vehicle-to-vehicle communications [28], [30], or multipathassisted localization [26], [27], [31], [34], which can use this information to improve their performance. To the best of our knowledge, none of the earlier referred 5G channel models currently considers birth-death processes for individual MPCs.…”

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confidence: 99%

Massive MIMO Extensions to the COST 2100 Channel Model: Modeling and Validation

Flordelis

Edfors

et al. 2020

IEEE Trans. Wireless Commun.

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To enable realistic studies of massive multiple-input multiple-output systems, the COST 2100 channel model is extended based on measurements. First, the concept of a base station-side visibility region (BS-VR) is proposed to model the appearance and disappearance of clusters when using a physically-large array. We find that BS-VR lifetimes are exponentially distributed, and that the number of BS-VRs is Poisson distributed with intensity proportional to the sum of the array length and the mean lifetime. Simulations suggest that under certain conditions longer lifetimes can help decorrelating closely-located users. Second, the concept of a multipath component visibility region (MPC-VR) is proposed to model birth-death processes of individual MPCs at the mobile station side. We find that both MPC lifetimes and MPC-VR radii are lognormally distributed. Simulations suggest that unless MPC-VRs are applied the channel condition number is overestimated. Key statistical properties of the proposed extensions, e.g., autocorrelation functions, maximum likelihood estimators, and Cramer-Rao bounds, are derived and analyzed. ). 2 I. INTRODUCTION Massive multiple-input multiple-output (MIMO), MaMi for short, has since its inception [3] attracted considerable attention in the wireless communication community [4]-[6]. Within the last few years, an abundant body of theoretical [5], [6] and experimental [7], [8] research has shown that MaMi systems can improve the energy and spectral efficiencies of today's wireless communication systems by one to two orders of magnitude. For this reason, MaMi is considered a crucial component of the new radio (NR) air interface of the fifth generation (5G) wireless communication standard [9].As is well known, the radio propagation channel ultimately dictates the performance of any wireless communication system. The availability of sufficiently accurate propagation channel models is therefore of critical importance to the design and evaluation of new wireless systems. The 3GPP SCM-3D [10], the WINNER II/WINNER+ [11], [12], and the COST 2100 [13], [14] are examples of channel models customarily used in the development and validation of 5G networks. Among them, the Quasi Deterministic Radio Channel Generator (QuaDRiGa) [15], [16], an extension of the 3GPP-3D and WINNER II/WINNER+ channel models, is especially popular because of its enhanced spatiotemporal consistency. Moreover, it possesses certain features that enable MaMi simulations, namely support for spherical wavefronts, dispersion of clusters in elevation, and independence of arrival/departure angles [16]. Experiment shows [17]-[19] that at least two additional aspects of the MaMi propagation channel need to be considered. The first of them [17], [18] is the presence at the base station (BS) of non-stationarities caused by the appearance and disappearance of clusters along physicallylarge arrays (PLAs). Such BS-side non-stationarities have been addressed in theoretical MaMi channel models [20], [21] in which the appearances and disappearances o...

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Massive MIMO Extensions to the COST 2100 Channel Model: Modeling and Validation

Flordelis

Edfors

et al. 2020

IEEE Trans. Wireless Commun.

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“…To obtain the SINRs, we apply (20) Fig. 12) obtained using (20) with the estimated amplitudes from (48). The column added contains the sum over all antennas, whereas the entry omni contains the results from [32] using an omni-directional antenna in the same setup.…”

Section: ) Measured Datamentioning

confidence: 99%

“…The works in [16], [17] consider the impact of estimating these map features on the Fisher information of the position and orientation error. In [20]- [24], simultaneous localization and mapping algorithms are presented that estimate the environment map from consecutive measurements, achieving accurate and robust position tracking of a mobile agent in challenging indoor environments. In [8], [25], the use of mm-wave antenna arrays was discussed for multipath-based indoor positioning.…”

Section: Introduction a Motivation And State Of The Artmentioning

confidence: 99%

Single-Anchor Positioning: Multipath Processing With Non-Coherent Directional Measurements

et al. 2020

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High-accuracy indoor radio positioning can be achieved by using (ultra) wideband (UWB) radio signals. Multiple fixed anchor nodes are needed to compute the position or alternatively, specular multipath components (SMCs) extracted from radio signals can be exploited. In this work, we study a multipath-based, single-anchor positioning system that acquires directional measurements non-coherently. These non-coherent measurements can be obtained, e.g., from a single-chain mm-wave transceiver with analog beam steering or from a low-complexity ultra-wideband transceiver with switched directional antennas. The directional antennas support the separation of SMCs and the suppression of the undesired diffuse multipath component (DMC) with the benefit that the required signal bandwidth can be drastically reduced. The paper analyzes the Cramér-Rao lower bound (CRLB) on the position estimation error to gain insight in the influence of the system design parameters as well as the impact of the DMC on the position error. The CRLB is compared between the non-coherent antenna setup, a conventional array with coherent processing, and a single-antenna setup. A maximum-likelihood position estimation algorithm is formulated. Its performance is evaluated with synthetically generated data as well as with UWB measurements. We show that the accuracy and robustness are significantly improved due to the processing of angular information. Analyzing the measured data for a line-of-sight link, the median error decreases from 22 down to 7 cm, the measurements better than 20 cm increase from 46 to 95 %, and outliers above 50 cm reduce from 12 to 0 %. INDEX TERMS Radio positioning, single-anchor, Fisher information, position error bound, directional antenna, multipath component, non-coherent array processing.

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“…By associating the estimated MPC parameters to VAs, these VAs can be used as additional PAs for location estimation. In recent years, many works that use wideband/ultra-wideband (UWB) signals have shown the potential of multipath-based positioning [20], tracking [21], [22] and simultaneous localization and mapping (SLAM) [23]- [26] with accuracy on a centimeter level. The works [27]- [29] use cooperation amongst agents to enhance multipath-assisted localization performance in infrastructure-limited scenarios.…”

Section: A State Of the Artmentioning

confidence: 99%

Massive MIMO-Based Localization and Mapping Exploiting Phase Information of Multipath Components

Leitinger

Oskarsson

et al. 2019

IEEE Trans. Wireless Commun.

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In this paper, we present a robust multipath-based localization and mapping framework that exploits the phases of specular multipath components (MPCs) using a massive multipleinput multiple-output (MIMO) array at the base station. Utilizing the phase information related to the propagation distances of the MPCs enables the possibility of localization with extraordinary accuracy even with limited bandwidth. The specular MPC parameters along with the parameters of the noise and the dense multipath component (DMC) are tracked using an extended Kalman filter (EKF), which enables to preserve the distancerelated phase changes of the MPC complex amplitudes. The DMC comprises all non-resolvable MPCs, which occur due to finite measurement aperture. The estimation of the DMC parameters enhances the estimation quality of the specular MPCs and therefore also the quality of localization and mapping. The estimated MPC propagation distances are subsequently used as input to a distance-based localization and mapping algorithm. This algorithm does not need prior knowledge about the surrounding environment and base station position. The performance is demonstrated with real radio-channel measurements using an antenna array with 128 ports at the base station side and a standard cellular signal bandwidth of 40 MHz. The results show that high accuracy localization is possible even with such a low bandwidth.Index Terms-Parametric channel estimation, extended Kalman filter, massive MIMO radio channel, localization and mapping.

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A Belief Propagation Algorithm for Multipath-Based SLAM

Cited by 186 publications

References 51 publications

Massive MIMO Extensions to the COST 2100 Channel Model: Modeling and Validation

Massive MIMO Extensions to the COST 2100 Channel Model: Modeling and Validation

Single-Anchor Positioning: Multipath Processing With Non-Coherent Directional Measurements

Massive MIMO-Based Localization and Mapping Exploiting Phase Information of Multipath Components

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