List of Wireless Communication IEEE 2014 Projects. It Contains the IEEE Projects in the Domain Wireless Communication for the year 2014

1. Wireless Communication IEEE 2014 Projects
Web : www.kasanpro.com Email : sales@kasanpro.com
List Link : http://kasanpro.com/projects-list/wireless-communication-ieee-2014-projects
Title :Map-Aware Models for Indoor Wireless Localization Systems: An Experimental Study
Language : C#
Project Link : http://kasanpro.com/p/c-sharp/map-aware-models-indoor-wireless-localization-systems
Abstract : The accuracy of indoor wireless localization systems can be substantially enhanced by map-awareness,
i.e., by the knowledge of the map of the environment in which localization signals are acquired. In fact, this knowledge
can be exploited to cancel out, at least to some extent, the signal degradation due to propagation through physical
obstructions, i.e., to the so called non-line-of-sight bias. This result can be achieved by developing novel localization
techniques that rely on proper mapaware statistical modelling of the measurements they process. In this manuscript a
unified statistical model for the measurements acquired in map-aware localization systems based on time-ofarrival
and received signal strength techniques is developed and its experimental validation is illustrated. Finally, the
accuracy of the proposed map-aware model is assessed and compared with that offered by its map-unaware
counterparts. Our numerical results show that, when the quality of acquired measurements is poor, map-aware
modelling can enhance localization accuracy by up to 110% in certain scenarios.
Title :Map-Aware Models for Indoor Wireless Localization Systems: An Experimental Study
Language : NS2
Project Link : http://kasanpro.com/p/ns2/map-aware-models-indoor-wireless-localization-systems-code
Abstract : The accuracy of indoor wireless localization systems can be substantially enhanced by map-awareness,
i.e., by the knowledge of the map of the environment in which localization signals are acquired. In fact, this knowledge
can be exploited to cancel out, at least to some extent, the signal degradation due to propagation through physical
obstructions, i.e., to the so called non-line-of-sight bias. This result can be achieved by developing novel localization
techniques that rely on proper mapaware statistical modelling of the measurements they process. In this manuscript a
unified statistical model for the measurements acquired in map-aware localization systems based on time-ofarrival
and received signal strength techniques is developed and its experimental validation is illustrated. Finally, the
accuracy of the proposed map-aware model is assessed and compared with that offered by its map-unaware
counterparts. Our numerical results show that, when the quality of acquired measurements is poor, map-aware
modelling can enhance localization accuracy by up to 110% in certain scenarios.