Node Localization with Simulated Proximity Graph Communication Model
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Node localization using simulated proximity relationship graphs for communication modeling. During node localization processes, we employ simulated proximity graphs to replicate communication models. This approach helps visualize node interaction patterns and achieves more accurate position estimation through localization algorithms. Typically implemented using neighborhood discovery protocols where nodes exchange beacon signals to determine relative distances, often utilizing received signal strength indicator (RSSI) or time-of-arrival (ToA) measurements. The graph structure represents communication ranges with edges indicating detectable node pairs, while graph connectivity analysis determines localization feasibility through techniques like multidimensional scaling or triangulation algorithms.
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