mmWaves RSSI indoor network localization

Vari, Marco; Cassioli, Dajana

doi:10.1109/iccw.2014.6881184

Cited by 48 publications

(42 citation statements)

References 11 publications

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“…The use of 5G technologies to obtain position and orientation was previously explored in [7]- [9] for mm-wave and in [10]- [12] for massive MIMO. The early work [7] considered estimation and tracking of DOA through beam-switching.…”

Section: Related Workmentioning

confidence: 99%

“…User localization was treated in [8], formulated as a hypothesis testing problem, limiting the spatial resolution. A different approach was taken in [9], where meter-level positioning accuracy was obtained by measuring received signal strength levels. In the massive MIMO case, [10] considered estimation of angles, while [11] treated joint estimation of delay, AOD, and AOA, and evaluated the impact of errors in delays and phase shifters.…”

Section: Related Workmentioning

confidence: 99%

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5G Position and Orientation Estimation through Millimeter Wave MIMO

Shahmansoori

Garcia

Destino

et al. 2015

2015 IEEE Globecom Workshops (GC Wkshps)

102

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Abstract-Millimeter wave and massive MIMO are considered enabling technologies for future 5G networks. While their benefits for achieving high-data rate communications are wellknown, their potential advantages for accurate positioning are largely undiscovered. We derive sufficient conditions under which transmission from a single mm-wave base station leads to a nonsingular Fisher information matrix associated with the position and orientation of a user terminal equipped with multiple antennas, which is in turn a prerequisite for joint estimation of the position and orientation.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

5G Position and Orientation Estimation through Millimeter Wave MIMO

Shahmansoori

Garcia

Destino

et al. 2015

2015 IEEE Globecom Workshops (GC Wkshps)

102

View full text Add to dashboard Cite

show abstract

“…LBS are always popular among the users and it is expected to become an essential part of the development of 5G technology. In [219], [220] the authors proposed localization techniques for millimeter waves in 5G. In [221]- [223] the authors presented localization schemes for massive multiple input multiple output (MIMO) systems.…”

Section: Mds Based Localization For Future 5gmentioning

confidence: 99%

“…DoA technique is investigated for 5G in [224]. Similarly, in [220], [225] the authors used localization based on RSS. An extended Kalman filter fused with the hybrid DoA and ToA is used in [226] for 5G localization.…”

Section: Mds Based Localization For Future 5gmentioning

confidence: 99%

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

Saeed

Nam

Al-Naffouri

et al. 2019

IEEE Commun. Surv. Tutorials

144

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Current and future wireless applications strongly rely on precise real-time localization. A number of applications such as smart cities, Internet of Things (IoT), medical services, automotive industry, underwater exploration, public safety, and military systems require reliable and accurate localization techniques. Generally, the most popular localization/ positioning system is the Global Positioning System (GPS). GPS works well for outdoor environments but fails in indoor and harsh environments. Therefore, a number of other wireless local localization techniques are developed based on terrestrial wireless networks, wireless sensor networks (WSNs) and wireless local area networks (WLANs). Also, there exist localization techniques which fuse two or more technologies to find out the location of the user, also called signal of opportunity based localization. Most of the localization techniques require ranging measurements such as time of arrival (ToA), time difference of arrival (TDoA), direction of arrival (DoA) and received signal strength (RSS). There are also range-free localization techniques which consider the proximity information and do not require the actual ranging measurements. Dimensionality reduction techniques are famous among the range free localization schemes. Multidimensional scaling (MDS) is one of the dimensionality reduction technique which has been used extensively in the recent past for wireless networks localization. In this paper, a comprehensive survey is presented for MDS and MDS based localization techniques in WSNs, Internet of Things (IoT), cognitive radio networks, and 5G networks. 2 MDS is much popular among all these techniques because of its simplicity and many application areas. MDS analysis finds the spatial map for objects given that the similarity or dissimilarity information between the objects is available [16].In the recent past, MDS is widely used for localization and mapping of wireless sensor networks (WSNs) and the internet of things (IoT). In [17] a proximity information based sensor network localization is proposed, where the main idea is to construct a local configuration of sensor nodes by using classical MDS (CMDS). The MDS based localization algorithms in [17] and [18] are centralized with higher computational complexity [7]. Semi-centralized (or clustered) MDS techniques are developed to compute local coordinates of nodes, which then are refined to find the final position of the nodes [19], [20]. In [21], [22] and [23] the authors proposed manifold learning to estimate the sensor nodes position in wireless sensor networks. In [24] the authors proposed Nystrom approximation for the proximity information matrix in MDS to reduce its size for better localization accuracy in sensor networks. Distributed MDS based localization algorithm is proposed in [25] with noisy range measurements, where the authors assume that the distances are corrupted with independent Gaussian random noise. MDS methods with different refinement schemes have also been proposed in the literature t...

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“…Research to date on 60 GHz ranging is incomplete and results are sparse [3] [4]. Therefore, there is a need to investigate 60 GHz ranging techniques for use in positioning systems.…”

Section: Introductionmentioning

confidence: 98%

Ranging performance with 60 GHz signals in indoor residential environments

Liu

Zhang

Gulliver

et al. 2015

2015 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)

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A 60 GHz ranging model is established and a strongest path search ranging algorithm based on beamforming is proposed. The range error caused by a non-line of sight (NLOS) channel is mitigated by modeling the corresponding delay bias. Outlier detection is employed to improve the accuracy. Performance results are presented which show that 60 GHz ranging can achieve centimeter level accuracy in indoor residential environments. The proposed range estimation algorithm results in an error of less than 5 cm 99% of the time in line of sight (LOS) channels, and an error of less than 10 cm 90% of the time in NLOS channels, over a distance of 5 m. This indicates that 60 GHz ranging is a practical and effective ranging solution.

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mmWaves RSSI indoor network localization

Cited by 48 publications

References 11 publications

5G Position and Orientation Estimation through Millimeter Wave MIMO

5G Position and Orientation Estimation through Millimeter Wave MIMO

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

Ranging performance with 60 GHz signals in indoor residential environments

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