carried out to retrieve people lost in the woods using mobile wireless communication, inhomogeneous vegetation environments have the special feature of acting as scatterers of electromagnetic waves. The signal scattering is translated into an excess of attenuation which can limit the performance of the Device-to-Device (D2D) communications envisaged at low power, high data rates and low latency expected for the upcoming 5G mobile wireless communications. D2D is expected to be used in almost every environment and scenario, and very especially in smart cells. The reduced coverage area and need for high data rate performance of this type of cell deployment can be limited by the attenuation due to vegetation. In fact, the appearance of the trees in the path of the communication link between the transmitter and the receiver has significant effects on the quality of the received signal. This is because a forest is characterized by vegetation of different canopies and components with different physical natures in terms of trees height, leaves pattern and thickness, trunk sizes and number of branches, which determine the rate of attenuation of radio waves that propagate through it via scattering, absorption, refraction and diffraction of the waves. The signal scattering is translated into an excess of attenuation which can limit the performance of the Internet of Things (IoT) envisaged at high data rates and low latency expected for the upcoming 5G mobile wireless communications. In this context, radio planning tasks become necessary in order to assess the validity of future D2D communications operating in vegetation environments. For that purpose, path loss models for scenarios with vegetation play a key role since they provide RF power estimations that allow an optimized design and performance of the wireless network [8]. Moreover, a path loss model may contribute to the evaluation of the maximum effective distance between adjacent terminals and hence to the estimation of the number of sensors needed to cover a certain area. Finally, the signal strength loss is related to the quality of service (QoS), causing unreliable communication between nodes that will increase both the number of data packet retransmissions and the power consumption of the nodes, causing radio link failure in last term. Therefore, there is a need for reliable through-vegetation radio channel modelling for vegetation environments, which will assess the propagation behavior in terms of both path loss and multipath propagation. Since the 1960s, a significant amount of work has been done to investigate the characterization of the radio channel blocked by vegetation elements [9; 10], which proposed different analytical and empirical models to estimate the power attenuation or level excess loss introduced by a signal blockage due to vegetation obstacles, mainly trees [9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23]. Among the conventional forest models, we can mention the COST 235 [11] and the Weissberger [12]. These models were developed to model the excess attenuation encountered in a forest beyond that predicted by either free-space or two-ray propagation. Moreover, the path loss was empirically modeled in [11; 13; 14; 15]. In [16; 17; 18], path loss models for a specific 1.9 GHz radio frequency are presented. More characteristics such as the shadowing loss [19] and small-scale fading [19; 20] for trees as well as tall food grass fields [21] were empirically modeled. In addition, a model for ultra-wideband (UWB) channels is presented in [22]. However, although a significant amount of research has been performed on the empirical propagation loss modeling, it is still a challenge to describe the radio wave propagation within the forest environment accurately. Especially in inhomogeneous vegetation environments, since a forest can be made up of mixed or homogeneous tree types resulting in different effects on radio waves even at the same frequency by the same group of trees, depending on the geometry of the link.