Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Voice Source Localization for Automatic Camera Pointing System in Videoconferencing
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Cognitive radio techniques for wide area networks
Proceedings of the 42nd annual Design Automation Conference
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
Energy-based sensor network source localization via projection onto convex sets
IEEE Transactions on Signal Processing
Overview of radiolocation in CDMA cellular systems
IEEE Communications Magazine
Implementation of collaborative RF localization using a software-defined radio network
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
ML aided context feature extraction for cognitive radio
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Most existing work on dynamic spectrum access deals with creating a spectral and temporal map of spectrum white space, and then filling it. The spectrum can be better utilized by increasing the spatial awareness of secondary users to include knowledge of the locations of all primary and secondary users, as well as the orientations and parameters of their directional or omni-directional antennas. This paper derives a Maximum Likelihood (ML) algorithm, an approximate ML algorithm, and associated performance bounds for jointly estimating a transmitter's position, orientation, beam width, and transmit power, as well as the environment's path loss exponent, using received signal strength measurements. The methods can be used for either a primary or secondary user. Simulations are used to determine what types of sensor geometries lead to good estimates of each parameter, to evaluate the performance of the estimators, and to determine spectrum availability as a function of spatial coordinates.