## 5 Simulation and Performance Analysis  
Network simulation results are heavily influenced by the selected propagation model, however, most of existing simulators adopt simplistic radio channel models. To further investigate the impact of near-ground propagation on network performance, the implementation of propagation models on a simulator is required. We adopted Cooja [19] as the simulation platform, which is a flexible Java-based simulator designed for WSNs running Contiki OS [24]. Cooja simulates sensor networks where each node can be of different type in terms of software and hardware. The simulated node platform was Tmote Sky (also known as TelosB). We used the Cooja simulator along with the MSPsim emulator [25], which provided accurate emulation in both cycle-level of the MSP430 micro-controller and bit-level of the CC2420 radio transceiver.  
We edited the simulation script and added the previously measured path loss models to Cooja. This enabled us to observe the network performance under actual scenarios.  
Differences in connectivity have a significant influence on the network communication. Many routing protocols are designed based on the assumption that a node has an exact knowledge of its neighbors. We tested the influence of different propagation models in network connectivity. The simulation scenario was the flat concrete road, with 5 cm height of transmitting and receiving antennas. The deployment area was 200 m \(\times\) 200 m, the transmitting power was +20 dBm, and the receive sensitivity was \(-\)100 dBm. We placed 50, 100, 150, and 200 nodes randomly over the deployment area, respectively, and calculated the average number of connectable neighbors in the transmission range of each node.  
The average percentage of connectivity is shown in Figure 10, expressed as the average ratio of the number of connectable neighbors to the total number of nodes. When the antenna height was 1 m, the connectivity ratio was obviously higher than the situation that when the antenna height was 5 cm. It is worth noting that, as the antenna height increased from 5 cm to 1 m, the path loss of two-ray model decreased significantly, and the connectivity ratio increased from about 15% to 100%. This indicates that, in near-ground scenarios, the two-ray model is extremely sensitive to antenna height, thus the path loss varies drastically with the change of antenna height. Therefore, the two-ray model has no universal applicability in this scenario. On the other hand, the free-space path loss model produced unrealistic value of path loss: the connectivity ratio remained 100% during the whole simulation, and, as a result, the transmission range was maintained at a level of over 300 m.  
Figure 9: Schematic diagram of the propagation model selection strategy.  
From another perspective, the results of simulation using simplistic theoretical models are far from the actual situation and are basically unusable in practical applications. The network performance and the designed protocol achieved in the simulation cannot be realized in practical applications because the connectivity of the network is significantly degraded in the actual scenario. Therefore, when designing and deploying a sensor network, it is important to use an accurate model based on real propagation characteristics in the simulation.