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Search Publications by: Kamran Sayrafian (Fed)

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Displaying 151 - 175 of 178

A Robust Model-Based Approach to Indoor Positioning Using Signal Strength

September 9, 2008
Author(s)
Kamran Sayrafian, Dominik Kasper
A simple technique to estimate the position of a mobile node inside a building is based on the Received Signal Strength (RSS). In previous publications, we investigated the effectiveness of using circular array antennas and beamforming in order to enable

Clustering Characteristics of Millimeter Wave Indoor Channels

April 8, 2008
Author(s)
Kamran Sayrafian, Behnam Neekzad, John Baras
Temporal-Angular channel sounding measurements of an indoor millimeter wave channel (60 GHz) is analyzed to determine whether ray arrivals at the receiver form clusters in the two-dimensional time-angle space. The channel behavior for directional antennas

Indoor Localization: Technology That Can Save First Responder Lives

December 1, 2007
Author(s)
Nader Moayeri, Camillo A. Gentile, Kamran Sayrafian, Michael R. Souryal
Every year a number of first responders lose their lives while battling fires or rescuing civilians during such emergencies. Indoor localization or location tracking roughly provides the same capability inside buildings that GPS does outdoors. It allows a

A Novel Model-Based Indoor Positioning Using Signal Strength

September 3, 2007
Author(s)
Kamran Sayrafian, D Kaspar
A simple technique to estimate the position of a mobile node inside a building is based on the Received Signal Strength (RSS). In a previous publication, we investigated the feasibility of using circular array antennas and beamforming in order to enable an

Robust Indoor Positioning Based on Received Signal Strength

July 10, 2007
Author(s)
Kamran Sayrafian, Julio Perez
RF-based indoor positioning is a challenging task due to the harsh indoor propagation environment. Techniques based on the received signal strength are simple to implement and offer low cost and effective alternatives for some applications. The main

Source-Assisted Direction Estimation Inside Buildings

April 11, 2006
Author(s)
Kamran Sayrafian, D Kaspar
Source direction estimation inside building is a difficult and challenging task due to severe multipath signal propagation. Numerous algorithms and techniques exist that provide high-resolution direction estimation under certain conditions and channel

Application of Beamforming in Wireless Location Estimation

January 1, 2006
Author(s)
Kamran Sayrafian, D Kaspar
We have implemented a quantum key distribution (QKD) system with polarization encoding at 850 nm over 1 km of optical fiber. The high-speed management of the bit-stream, generation of random numbers and processing of the sifting algorithm are all handled

Source-Assisted Direction Estimation Inside Buildings

January 1, 2006
Author(s)
Kamran Sayrafian, D Kaspar
We have implemented a quantum key distribution (QKD) system with polarization encoding at 850 nm over 1 km of optical fiber. The high-speed management of the bit-stream, generation of random numbers and processing of the sifting algorithm are all handled

Indoor Positioning Using Spatial Power Spectrum

October 1, 2005
Author(s)
Kamran Sayrafian, D Kaspar
A simple technique to estimate the position of a given mobile source inside a building is based on the received signal strength. For this methodology to have a reasonable accuracy, radio visibility of the mobile by at least three access points is required

Indoor Positioning Using Spatial Spectrum

September 7, 2005
Author(s)
Kamran Sayrafian
We have implemented a quantum key distribution (QKD) system with polarization encoding at 850 nm over 1 km of optical fiber. The high-speed management of the bit-stream, generation of random numbers and processing of the sifting algorithm are all handled

Application of Beamforming in Wireless Location Estimation

July 1, 2005
Author(s)
Kamran Sayrafian
We have implemented a quantum key distribution (QKD) system with polarization encoding at 850 nm over 1 km of optical fiber. The high-speed management of the bit-stream, generation of random numbers and processing of the sifting algorithm are all handled