Radio propagation modeling and real test of ZigBee based indoor wireless sensor networks

The deployment of nodes in Wireless Sensor Networks (WSNs) arises as one of the biggest challenges of this field, which involves in distributing a large number of embedded systems to fulfill a specific application. The connectivity of WSNs is one of the main issues to assure the efficiency of the system implementation and the quality of the service of the deployment, which is difficult to estimate due to the diversity and irregularity of the applied environment and it affects the WSN designers' decision on deploying sensor nodes. Therefore, in this paper, a new method is proposed to enhance the efficiency and accuracy on ZigBee propagation modeling and simulation in indoor environments. The method consists of two steps: automatic 3D indoor reconstruction and 3D ray-tracing based radio simulation. The automatic 3D indoor reconstruction employs unattended image classification algorithm and image vectorization algorithm to accurately build the environment database, which also significantly reduces time and efforts spent on non-radio propagation issues. The 3D ray tracing is developed by using a kd-tree space division algorithm and a modified polar sweep algorithm, which accelerates the searching of rays over the entire space. A ZigBee signal propagation model is proposed for the ray-tracing engine by considering both the materials of obstacles and the impact of positions along the ray path of the radio. Three different WSN deployments are realized in the indoor environment of an office and the simulation results are verified to be accurate. Experimental results also indicate that the proposed method is efficient in the pre-simulation strategy and the 3D ray searching scheme, and it is robust for different indoor environments.