Analysis of the urban/rural broadband divide in Canada: Using GIS in planning terrestrial wireless deployment

Sawada, M.; Cossette, Daniel; Wellar, Barry; Kurt, Tolga

doi:10.1016/j.giq.2006.08.003

Cited by 48 publications

(20 citation statements)

References 13 publications

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“…Wireless broadband comes in many forms, connecting a home or business to the internet without wires, typically via a radio link between a customer's location and a facility operated by a service provider (Sawada, Cossette, Wellar, & Kurt, 2006). A simple typology to differentiate between types of wireless broadband is fixed and mobile.…”

Section: Wireless Broadband In the United Statesmentioning

confidence: 99%

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The wireless abyss: Deconstructing the U.S. National Broadband Map

Grubesic

2012

Government Information Quarterly

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Section: Wireless Broadband In the United Statesmentioning

confidence: 99%

“…While there is no doubt that the number of smart devices leveraging wireless broadband networks is on the rise, the ubiquity of wireless broadband is less certain (Middleton & Bryne, 2011;Sawada et al, 2006). Fig.…”

Section: Wireless Broadband In the United Statesmentioning

confidence: 99%

The wireless abyss: Deconstructing the U.S. National Broadband Map

Grubesic

2012

Government Information Quarterly

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“…Therefore, we form sensor clusters among the sensors in close proximity such that sensors within the same cluster are highly correlated. A measurement study in [38] indicates that households in rural areas tend to be clustered, and thus, it is reasonable to assume that a BS can identify several sensor (i.e., CPE) clusters within its own cell of typical radius of 33 km. If such a sensor cluster exists, the BS can easily identify them based on their location information.…”

Section: Cluster-based Hypothesis Testingmentioning

confidence: 99%

Secure Cooperative Sensing in IEEE 802.22 WRANs Using Shadow Fading Correlation

Min

Shin

2011

IEEE Trans. on Mobile Comput.

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Abstract-Cooperative (or distributed) sensing has been recognized as a viable means to enhance the incumbent signal detection by exploiting the diversity of sensors. However, it is challenging to secure such distributed sensing due mainly to the unique features of dynamic spectrum access networks-openness of low-layer protocol stacks in software-defined radio devices and the absence of interactions/coordination between primary and secondary devices. To meet this challenge, we propose an attack-tolerant distributed sensing protocol (ADSP) for DTV signal detection in IEEE 802.22 WRANs, under which sensors in close proximity are grouped as a cluster, and sensors within a cluster cooperate to safeguard the integrity of sensing. The heart of ADSP is a novel filter based on shadow-fading correlation, by which the fusion center cross-validates reports from the sensors to identify and penalize abnormal sensing reports. By realizing this correlation filter, ADSP significantly reduces the impact of an attack on the performance of distributed sensing, while incurring minimal processing and communication overheads. ADSP also guarantees the detectability requirements of 802.22 to be met even with the presence of sensing report manipulation attacks by scheduling sensing within the framework of sequential hypothesis testing. The efficacy of ADSP is validated on a realistic two-dimensional shadow-fading field. Our extensive simulation-based study shows that ADSP reduces the false-alarm rate by 99.2 % while achieving 97.4 % of maximum achievable detection rate, and meets the detection requirements of IEEE 802.22 in various attack scenarios.

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“…They also have applications in wireless communication (Sawada et al, 2006) and land cover map generation (Caccetta et al, 2015). It is popular to generate DEMs using remote sensors including light detection and ranging sensors (LiDAR), digital stereo (multiple view)-photography, and interferometric synthetic aperture radar (InSAR).…”

Section: Introductionmentioning

confidence: 99%

Digital Terrain From a Two-Step Segmentation and Outlier-Based Algorithm

Hingee¹,

Caccetta²,

Caccetta³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:We present a novel ground filter for remotely sensed height data. Our filter has two phases: the first phase segments the DSM with a slope threshold and uses gradient direction to identify candidate ground segments; the second phase fits surfaces to the candidate ground points and removes outliers. Digital terrain is obtained by a surface fit to the final set of ground points. We tested the new algorithm on digital surface models (DSMs) for a 9600km 2 region around Perth, Australia. This region contains a large mix of land uses (urban, grassland, native forest and plantation forest) and includes both a sandy coastal plain and a hillier region (elevations up to 0.5km). The DSMs are captured annually at 0.2m resolution using aerial stereo photography, resulting in 1.2TB of input data per annum. Overall accuracy of the filter was estimated to be 89.6% and on a small semi-rural subset our algorithm was found to have 40% fewer errors compared to Inpho's Match-T algorithm.

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Analysis of the urban/rural broadband divide in Canada: Using GIS in planning terrestrial wireless deployment

Cited by 48 publications

References 13 publications

The wireless abyss: Deconstructing the U.S. National Broadband Map

The wireless abyss: Deconstructing the U.S. National Broadband Map

Secure Cooperative Sensing in IEEE 802.22 WRANs Using Shadow Fading Correlation

Digital Terrain From a Two-Step Segmentation and Outlier-Based Algorithm

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