Re-establishing network connectivity in post-disaster scenarios through mobile cognitive radio networks

Trotta, A.; Felice, Marco Di; Bedogni, Luca; Bononi, Luciano

doi:10.1109/medhocnet.2013.6767405

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…Probability of detecting an emergency user except the PU can be expressed as

Pr ((), {italicSINR}_{\min}) = Pr ((), italicSINR < T_{italicth 2}) = Pr ((), \frac{{SNR}_{c} \times L ((), r cos θ)}{1 + {INR}_{c}} < T_{italicth 2})

where

{INR}_{c} = \frac{P_{c}}{N_{0} R_{0}^{γ} {(1 + d_{italicopt})}^{γ}}

is the interference to noise ratio of controller P c is the interference power. R 0 is the distance between controller and the primary transmitter. d opt is the optimal distance between controller and SUs.

Pr ((), {italicSINR}_{\min}) = Pr ((), d_{opt} < ({}, \frac{1}{R_{o}} {[\frac{{SNR}_{c} \times T_{th}}{{SNR}_{s} \times L ((), r cos θ) - T_{th}}]}^{\frac{1}{γ}} - 1))

where SNR s is the signal to noise ratio of SU/emergency user, T th is the threshold SINR at which secondary recognizes a primary signal, and SNR c is the signal to noise ratio at the secondary receiver SR 1 due to data transmission from controller.…”

Section: Estimation Of Emergency User Using Fixed Sensing Rangementioning

confidence: 99%

“…They addressed main challenges including mobility management and coverage life time. Angello Trotta explored the utilization of Stem Nodes with self‐positioning and dynamic routing functionalities, and thus replaces the damaged components of the original infrastructure. Authors looked into the problem of determining the optimal deployment of SNs.…”

Section: Introductionmentioning

confidence: 99%

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A novel approach of user existence awareness using adaptive spectrum sensing controllers in emergency‐based cognitive radio adhoc networks

Sudhakaran¹,

Suganthi²

2018

Int J Communication

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Summary Spectrum sharing can be considered as an alternative solution to overcome spectrum limitation. Cognitive radio is the most important spectrum sharing technique in wireless communication system, which aims to enhance the utilization of radio frequency spectrum. Identification of spectrum environments like location of both licensed and unlicensed users has been considered in cognitive radio technology. In this paper, cognitive controller is an emergency repairing unit, which is introduced to maximize the number of connected users in an emergency situation. The analysis shows that the sensing efficiency of fixed sensing controller to identify users is limited to its sensing region. A hybrid technique with overlay and underlay accessing to perform data offloading in emergency situations and to connect the disconnected users is proposed to enhance the location sensing efficiency of the controller. A cognitive user node located at the interference region of controller experiences hidden node problem and causes interference to other users. In order to identify such users, an adaptive and cooperative sensing‐based controller is proposed, and efficiency of which is compared with the efficiency of fixed sensing controller. Theoretical and simulation analysis explores that the sensing capacity of adaptive sensing controller provides 42% of higher efficiency than the fixed sensing method.

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“…Probability of detecting an emergency user except the PU can be expressed as

Pr ((), {italicSINR}_{\min}) = Pr ((), italicSINR < T_{italicth 2}) = Pr ((), \frac{{SNR}_{c} \times L ((), r cos θ)}{1 + {INR}_{c}} < T_{italicth 2})

where

{INR}_{c} = \frac{P_{c}}{N_{0} R_{0}^{γ} {(1 + d_{italicopt})}^{γ}}

Pr ((), {italicSINR}_{\min}) = Pr ((), d_{opt} < ({}, \frac{1}{R_{o}} {[\frac{{SNR}_{c} \times T_{th}}{{SNR}_{s} \times L ((), r cos θ) - T_{th}}]}^{\frac{1}{γ}} - 1))

Section: Estimation Of Emergency User Using Fixed Sensing Rangementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A novel approach of user existence awareness using adaptive spectrum sensing controllers in emergency‐based cognitive radio adhoc networks

Sudhakaran¹,

Suganthi²

2018

Int J Communication

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“…More specifically, we consider an emergency scenario, where not all End-User (EU) devices are connected to each other, and the aerial mesh attempts to build the links between them. Three contributions are provided: (i) We extend our earlier distributed algorithm in [15] [16] in the context of a swarm of SUAVs, that allows them to self-organize into an aerial mesh to maximally connect the EUs on the ground. The mobility scheme is based on the Virtual Spring force model [14], and introduces channel-aware metrics in order to guarantee a minimum link quality on the air-to-ground and air-to-air links.…”

Section: Introductionmentioning

confidence: 99%

Self-organizing aerial mesh networks for emergency communication

Felice

Trotta

Bedogni

et al. 2014

2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC)

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Abstract-Guaranteeing network connectivity in post-disaster scenarios is challenging yet crucial to save human lives and to coordinate the operations of first responders. In this paper, we investigate the utilization of low-altitude aerial mesh networks composed by Small Unmanned Aerial Vehicles (SUAVs) in order to re-enstablish connectivity among isolated end-user (EU) devices located on the ground. Aerial ad-hoc networks provide the advantage to be deployable also on critical scenarios where terrestrial mobile devices might not operate, however their implementation is challenging from the point of view of mobility management and of coverage lifetime. In this paper, we address both these issues with three novel research contributions. First, we propose a distributed mobility algorithm, based on the virtual spring model, through which the SUAV-based mesh node -called also Repairing Units (RUs) in this study-can self-organize into a mesh structure by guaranteeing Quality of Service (QoS) over the aerial link, and connecting the maximum number of EU devices. Second, we evaluate our scheme on a realistic 3D environment with buildings, and we demonstrate the effectiveness of the aerial deployment compared to a terrestrial one, in terms of coverage and wireless link reliability. Third, we address the problem of energy lifetime, and we propose a distributed charging scheduling scheme, through which a persistent coverage of RUs can be guaranteed over the emergency scenario.

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Enhancing Cooperative Spectrum Sensing in Flying Cell Towers for Disaster Management Using Convolutional Neural Networks

Suriya

Sumithra

2019

EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing

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Re-establishing network connectivity in post-disaster scenarios through mobile cognitive radio networks

Cited by 6 publications

References 17 publications

A novel approach of user existence awareness using adaptive spectrum sensing controllers in emergency‐based cognitive radio adhoc networks

A novel approach of user existence awareness using adaptive spectrum sensing controllers in emergency‐based cognitive radio adhoc networks

Self-organizing aerial mesh networks for emergency communication

Enhancing Cooperative Spectrum Sensing in Flying Cell Towers for Disaster Management Using Convolutional Neural Networks

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