High Order Geometric Range Free Localization in Opportunistic Cognitive Sensor Networks

Gong, Dian; Ma, Zhiyao; Li, Yunfan; Chen, Wei; Cao, Zhigang

doi:10.1109/iccw.2008.31

Cited by 17 publications

(6 citation statements)

References 11 publications

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“…In cognitive sensor networks (CSN), location information of the primary user (PU) is important for secondary users (SU) in order to efficiently utilize spatial spectrum while protecting primary communication. Some schemes have been proposed on primary user localization in the context of CSN [32]- [34]. The proposed schemes [32]- [34] differ from our work in two aspects.…”

Section: Related Workmentioning

confidence: 45%

“…Some schemes have been proposed on primary user localization in the context of CSN [32]- [34]. The proposed schemes [32]- [34] differ from our work in two aspects. First of all, they usually assume that the secondary network is an infrastructure-based network, such as an IEEE 802.11 WRAN, in which each cell consists of a central processing point, e.g., a base station, to fuse the information to estimate the position of the PU.…”

Section: Related Workmentioning

confidence: 45%

“…First of all, they usually assume that the secondary network is an infrastructure-based network, such as an IEEE 802.11 WRAN, in which each cell consists of a central processing point, e.g., a base station, to fuse the information to estimate the position of the PU. Secondly, the proposed schemes either focus on the tracking of only one mobile PUs location after its detection [34] or assume the primary users are almost stationary [32], [33].…”

Section: Related Workmentioning

confidence: 99%

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On Non-Cooperative Multiple-Target Tracking With Wireless Sensor Networks

Zhu

Vikram

et al. 2014

IEEE Trans. Wireless Commun.

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Abstract-In this paper, we propose an approach to track multiple non-cooperative targets with wireless sensor networks. Most existing tracking algorithms can not be directly applied to non-cooperative target tracking because they assume the access to signals from individual targets for tracking by assuming that: 1) there is only one target in a field; 2) signals from different cooperative targets can be differentiated; or 3) interference caused by signals from other targets is negligible because of attenuation. We propose a general approach for tracking non-cooperative targets. The tracking algorithm first separates the aggregate signals from multiple indistinguishable targets via the blind source separation (BSS) algorithms. Through the analysis on both the temporal and spatial correlation of the separated individual signals, the tracking algorithm determines the location of a target and its moving track. A voting scheme based on the spatial information is designed to better estimate the moving track. Furthermore, we analyze and discuss the influence of signal attenuation and the tracking resolution of the proposed tracking approach. Our experiments show that the proposed approach can both accurately and precisely track multiple indistinguishable moving targets.

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Section: Related Workmentioning

confidence: 45%

Section: Related Workmentioning

confidence: 45%

Section: Related Workmentioning

confidence: 99%

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On Non-Cooperative Multiple-Target Tracking With Wireless Sensor Networks

Zhu

Vikram

et al. 2014

IEEE Trans. Wireless Commun.

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“…For instance, Ref. [6] proposed a high order geometric rangefree algorithm, while Ref. [7] resorted to a range-based algorithm assuming precise knowledge of the received signal strength (RSS) information from PUs.…”

Section: Introductionmentioning

confidence: 99%

Location-aware downlink and uplink power control and throughput optimization in cellular cognitive radio networks

Chen

Cao

et al. 2010

Front. Electr. Electron. Eng. China

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In this paper, we consider throughput maximization in cognitive radio systems with proper power control. In particular, we incorporate location-awareness into the power control design and maximize the average throughput of the cognitive system. As we shall show, the proposed approach effectively utilizes the "spatial opportunity" to maximize the system throughput, which clearly outperforms traditional power control methods. Further, the proposed approach still exhibits significant throughput gain even considering imperfect position information, with appropriate robust design modifications.

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“…As it is shown in Figure 7, an order-based geometric range free localization is proposed with two steps: 1st order geometric location and high order geometric localization [16].…”

Section: Figure 7 Range-free Localizationmentioning

confidence: 99%