A hidden environment model for constructing indoor radio maps

Constructing indoor radio maps plays an important role in many services and applications, such as wireless base station planning. We propose a hybrid approach to constructing indoor radio maps by developing a novel indoor signal propagation model, called the hidden environment model (HEM). The model is hybrid because it combines on-site measurements with a number of different types of calculations. As part of this model, we introduce the idea of an environment factor matrix (EFM). The EFM represents a model of the environmental features that affect radio attenuation. We also develop a lazy sampling algorithm to help generate the EFM. The goal of the lazy sampling algorithm is to balance the number of measurements that need to be taken with our model's accuracy. The goal is to minimize the measurement workload while maintaining satisfactory accuracy. We evaluate our model by comparing the radio maps calculated from the model to a radio map obtained by exhaustive measurements. The results show that our hidden environment model achieves good accuracy.