A multi-stage methodology is presented that combines ray-tracing RF predictions with spectral embedding and balanced k-means clustering to design clustered static wireless mesh networks under path-loss constraints.
Architecture and Eval- uation of an Unplanned 802.11b Mesh Network,
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A Machine Learning Framework for Large-Scale Static Wireless Mesh Networks
A multi-stage methodology is presented that combines ray-tracing RF predictions with spectral embedding and balanced k-means clustering to design clustered static wireless mesh networks under path-loss constraints.