Path loss results for wireless sensor network deployment in a sparse tree environment

This paper presents a large dataset of radio frequency (RF) measurements for wireless sensor network (WSN) deployment in a sparse tree environment. Such measurements are typically made for a better evaluation and understanding of signal attenuation in different propagation environments. Given the sophistication of theoretical path loss (PL) model derivation for such random environments, an empirical PL model is rather derived from in-field measurements for the specific field. In this paper, the empirical PL model has already been presented in a previous work. However, more details on model derivation as well as the variations of received signal strength (RSS) for eight different distances are provided. In addition, the empirical PL model of the investigated environment is compared with five empirical models of WSN, which are sand terrain, concrete surface, sparse tree, dense tree, and artificial turf. The results from the comparison of these different environments show significant differences in PL prediction, PL exponents, and variation elements. Furthermore, the empirical model is compared with popular theoretical models (i.e., free space PL and two-ray models), where the comparison shows an inaccuracy of these theoretical models in predicting RSS in WSN deployment in sparse tree environments.