Omnidirectional Mobile NLOS Identification and Localization via Multiple Cooperative Nodes

Wang, Zhonghai; Zekavat, S.A.

doi:10.1109/tmc.2011.232

Cited by 54 publications

(35 citation statements)

References 21 publications

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“…Due to this feature, the TACM algorithm is actually very strong in defending inappropriate DOA classifications. 4) Impact of the DOA Estimation Error: In some applications in the past, the accuracy of DOA estimation has proved problematic [14], [15]. However, as mentioned before, the probability of having NLOS is low in the investigated SCN scenario and the accuracy of DOA estimation can be very high.…”

Section: Impact Of Performance Related Parametersmentioning

confidence: 90%

“…In spite of this, attention still has to be paid to the resolution property of DOA estimation which depends upon the SNR, the number of elements in the array, the number of snapshots, the array geometry and so on [12]. Although, DOA estimation is more effective for line-of-sight (LOS) paths, research is also ongoing to deal with the influence of non-line-of-sight (NLOS) paths [14], [15]. In the SCN scenario investigated in this paper, the transmission path between a UE and an eNB is usually short and is more likely to be LOS so that DOA estimation can potentially have high accuracy.…”

Section: B Main Contributionsmentioning

confidence: 99%

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Traffic-Aware Cell Management for Green Ultradense Small-Cell Networks

Grace

Mitchell

2017

IEEE Trans. Veh. Technol.

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To reduce the power consumption of 5G ultradense small cell networks, base stations can be switched to low power sleep modes when local traffic levels are low. In this paper, a novel sleep mode control algorithm is proposed to control such sleep modes. The algorithm innovates a concept called Traffic-Aware Cell Management (TACM). It involves cell division, cell death and cell migration to represent adaptations of networks, where state transitions of base stations are controlled. Direction of arrival is adopted for distributed decision making. The TACM algorithm aims at reducing the network power consumption while alleviating the impacts of applying sleep modes, such as mitigating system overheads and reducing user transmission power. The TACM algorithm is compared with a recent consolidated baseline scheme by simulation on networks with unbalanced traffic distributions and with base stations at random locations. In contrast, the TACM algorithm shows a significant improvement in mitigating system overheads due to no load information exchange overhead and up to 72 times less switching frequency. Up to 81% network power consumption can be reduced compared with the baseline scheme if considering high energy consumption of switching transient states. In addition, at a low traffic level, average uplink transmission power is reduced by 79% comparatively. Furthermore, the impact of important performance governing parameters of the TACM algorithm is analysed. The insensitivity to the estimation accuracy of direction of arrival is also demonstrated. The results show that the proposed TACM algorithm has a comprehensive advantage of power reduction and overhead mitigation over the baseline scheme.

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Section: Impact Of Performance Related Parametersmentioning

confidence: 90%

Section: B Main Contributionsmentioning

confidence: 99%

Traffic-Aware Cell Management for Green Ultradense Small-Cell Networks

Grace

Mitchell

2017

IEEE Trans. Veh. Technol.

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show abstract

“…To address the localization problem in the multipath environment, many two-step processing methods have been developed, [5][6][7][8][9][10] where the measurement parameters (e.g. direction of arrival (DOA) and time of arrival (TOA)) of the multipath signals are first extracted and then the source positions are estimated using statistical or parametric methods.…”

Section: Introductionmentioning

confidence: 99%

Reflector-aided direct locations of multiple signals in the presence of small reflector position biases

Yin

Wang

et al. 2018

International Journal of Distributed Sensor Networks

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Direct position determination (DPD) is a single-step method that localizes transmitters from sensor outputs without computing intermediate parameters. It outperforms conventional two-step localization methods, especially under low signal-to-noise ratio conditions. This article proposes a reflector-aided DPD algorithm for multiple signals of known waveforms received by an array observer. In previous studies, reflector-aided localization has always required very precise locations of reflectors. Therefore, the localization performance depends sensitively on accurately knowing each reflector position. This study considers the presence of small biases in reflector locations. To make the problem tractable, we simplify the signal model through an approximation using the first-order Taylor expansion and then directly localize multiple sources in a decoupled manner. Unlike most DPDs that presume noise is spatially uncorrelated, our study imposes no restriction on the correlation structure of noise, allowing this algorithm to be used in more general scenarios. In addition, we derive the Cramér-Rao bound expression and perform an analysis of the direct locations of multiple signals when the reflector positions are assumed accurate but in fact have small biases. Simulation results corroborate the theoretical results and a good localization performance of the proposed algorithm in the presence of small reflector position biases.

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“…The non-line of sight identification techniques have been discussed extensively in the literature, but mainly within the cellular network framework [7][8][9][10][11][12][13]. For example, in [10], the authors address the NLOS identification problems based on the multiple received signal strength measurements from Wi-Fi signals.…”

Section: Introductionmentioning

confidence: 99%

NLOS Identification Based on Energy Receiver Using IEEE 802.15.3c

Zhang¹,

Zhang²,

Liang³

2016

Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering

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Abstract. Non-line-of-sight (NLOS) is the major problem for the indoor localization. So as to deal with NLOS propagation, a novel NLOS identification method is proposed based on the skewness and slope of the (energy detection) ED-based received energy block. IEEE 802.15.3c 60 GHz channel models are used as examples to be explained in detail. The proposed approach relies on the ED-based parameters which make it simple. Numerical simulations results show that the accuracy of NLOS identification up to 80% which is higher than other ED-based NLOS identification.

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Omnidirectional Mobile NLOS Identification and Localization via Multiple Cooperative Nodes

Cited by 54 publications

References 21 publications

Traffic-Aware Cell Management for Green Ultradense Small-Cell Networks

Traffic-Aware Cell Management for Green Ultradense Small-Cell Networks

Reflector-aided direct locations of multiple signals in the presence of small reflector position biases

NLOS Identification Based on Energy Receiver Using IEEE 802.15.3c

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