Localization by Compressive Sensing
Submission Deadline: Jan. 30, 2015
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Technology and Research in Emerging Networks and Distributed Systems (TRENDS), Information Technology University (ITU), Lahore, Punjab, Pakistan
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Published Papers
Authors: A. Ali
Pages: 1-5 Published Online: Nov. 29, 2014
Views 4200 Downloads 353
When a disaster strikes in an unexpected condition, the outcomes we face are very unfortunate. In this scenario a victim who has survived during the catastrophe condition tends to develop unawareness and unconscious feelings. In this mental and physical condition he or she neither could call anyone on mobile nor receive any call or message, even if the network is available in the respective area, although the chances are very rare. In this scenario finding the victims is the priority necessity of the rescue operation. Previously there have been a number of defined and proposed localization algorithms, whose effectiveness depends on the availability of time, resources and environment. Since the priority area of deployment of proposed PPDR infrastructure is for not only for developed environment but also for rural area, here neither robotic sensor can be used nor could Satellite and GPS effective localizations techniques be implemented. In this situation, the chosen localization technique senses power from a victim’s mobile through wireless signals. Later the responses from the victim mobile are estimated at frequencies by using Discrete Time Fourier Transform.


Where N is number of time domain samples. By using Kalman filter, to predict the location of change more accurately according to the moving pattern if any.

Previously there have been proposed techniques for disaster relief networks, but the drawback with the present technique is the incapability to adapt to single node environment architecture with comparison to multi node. Thereby the chosen technique will have the ability to apply collaborative compressive spectrum sensing in the situation where the requesting nodes are in numbers and would also have the adaptability to use compressive spectrum sensing where a single user resides alone. Along with providing localization facility for mobile user.
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