Information about primary user (PU) location is crucial in enabling several key capabilities in dynamic spectrum access networks, including improved spatio-temporal sensing, intelligent location-aware routing, as well as aiding spectrum policy enforcement. Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only  received signal strength information, which makes it simple  and robust to variations in the propagation environment. In contrast to prior work, which focused mainly on proposing algorithmic variations and verifying their performance through simulations, in this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance and correlation distance. Using this analysis, we quantify the robustness of WCL to various physical conditions and provide  guidelines, such as node placement, for  practical deployment of WCL. We also propose a practical method for employing WCL through a distributed cluster-based implementation. This approach achieves comparable accuracy with its centralized counterpart, and greatly reduces transmit power consumption .
Information about primary transmitter location is crucial in enabling several key capabilities in dynamic spectrum access networks, including improved spatio-temporal sensing, intelligent location-aware routing, as well as aiding spectrum policy enforcement. Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only the received signal strength information, which makes it simple to implement and robust to variations in the propagation environment. In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance and correlation distance. Using this analysis, we quantify the robustness of WCL to various physical conditions and provide design guidelines, such as node placement, for the practical deployment of WCL. We also propose a practical method for employing WCL through a distributed cluster-based implementation. This approach achieves comparable accuracy with its centralized counterpart, and greatly reduces total transmit power .
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user (PU)
transmitter
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the
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to implement
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contrast to prior work, which focused mainly on proposing algorithmic variations and verifying their performance through simulations, in
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design
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the
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transmit power consumption
total transmit power