Prediction technique on the effect of human motion on indoor radio wave propagation / Md. Jakirul Islam - Md. Jakirul , Islam (2013)
Due to the attractive features of millimeter band, its uses are greatly expanding in the indoor wireless communication systems. As the distance between the transmitter and receiver is much shorter in indoor environments than that of the outdoor environment, the radio wave paths of the millimeter band frequencies are highly influenced by the building materials as well as by the human movements. Ray tracing is widely used method to characterize the radio wave propagation for the planning and establishment of the indoor wireless network. Accurate object modeling for the realistic environment and computational time are two classical problems of the ray tracing model. Because, large number of rays that travels in a complex and convoluted indoor environment must be traced. Therefore, an accurate and efficient ray tracing method is proposed here, which is based on the surface separation, object address distribution and surface skipping techniques. The proposed approach considers the effects of human body movement to provide a realistic estimation of the wave propagation. Hence, an approximated human body model is proposed to simulate the activities of humans, whereas three dimensional (3-D) cube or cuboids are used for the remaining objects of the simulation environment. The Red-Black tree data structure provides a faster object retrieval mechanism while object address distribution technique prevents the unnecessary objects to take part in intersection tests, thus accelerates the ray tracing. Conversely, the surface separation is a novel technique that makes the tracing of the ray paths easily and accurately, mostly for the complex 3-D environment. In addition, the calculation of exact ray paths that reach the receiver after multiple reflections, refractions and/or diffractions is also considered in this study. To prove the superiority, complexity analysis and detail comparisons (based on predicted rays, computational time and received power) between the proposed and existing methods are presented in this study. It is observed from the results that the proposed method predicts the same amount of rays and received power as the image and Space Volumetric Partitioning (SVP) methods, which ensures the accuracy of the proposed method. Conversely, the proposed method predicts the higher amount of rays (it is about 10% and 2%) and higher amount of received power (it is about 3.65% and 1.87%) compared to the Ray Launching (RL) and Angular Z-Buffer (AZB) methods, respectively. Moreover, the proposed method is 30.75%, 36.47, 69.30%, and 91.47% faster than the SVP, AZB, Image, and RL methods, respectively, when the simulation was carried out in the simple and complex environment, respectively. Additionally, the proposed method relatively obtaining the constant time for two different environments and the simulation time does not directly follow the number of objects of the indoor environment. The results obtained will be of great interest for the proposed ray tracing method that involves human motion within the simple and complex indoor environments.