A path loss prediction formula for IoT (Internet of Things) wireless communication close to ceiling beams in the 920MHz band is presented. In first step of our investigation, we conduct simulations using the FDTD (Finite Difference Time Domain) method and propagation tests close to a beam on the ceiling of a concrete building. In the second step, we derive a path loss prediction formula from the simulation results by using the FDTD method, by dividing into three regions of LoS (line-of-sight) situation, situation in the vicinity of the beam, and NLoS (non-line-of-sight) situation, depending on the positional relationship between the beam and transmitter (Tx) and receiver (Rx) antennas. For each condition, the prediction formula is expressed by a relatively simple form as a function of height of the antennas with respect to the beam bottom. Thus, the prediction formula is very useful for the wireless site planning for the IoT wireless devices set close to concrete beam ceiling.

Basic characteristics for relating design and base station layout design in land mobile communications are provided through a propagation model for path loss prediction. Owing to the rapid annual increase in traffic data, the number of base stations has increased accordingly. Therefore, propagation models for various scenarios and frequency bands are necessitated. To solve problems optimization and creation methods using the propagation model, a path loss prediction method that merges multiple models in machine learning is proposed herein. The method is discussed based on measurement values from Kitakyushu-shi. In machine learning, the selection of input parameters and suppression of overlearning are important for achieving highly accurate predictions. Therefore, the acquisition of conventional models based on the propagation environment and the use of input parameters of high importance are proposed. The prediction accuracy for Kitakyushu-shi using the proposed method indicates a root mean square error (RMSE) of 3.68dB. In addition, predictions are performed in Narashino-shi to confirm the effectiveness of the method in other urban scenarios. Results confirm the effectiveness of the proposed method for the urban scenario in Narashino-shi, and an RMSE of 4.39dB is obtained for the accuracy.

Modification of ITU-R P.1411 model to enhance the prediction accuracy in urban environments having variable heights of buildings is proposed in this paper by introducing two kinds of novel correction factors. One is considering the relationship of the highest building height and the transmitter (Tx) antenna height, and the other is considering the effect of receiver (Rx) position on crossroads. After introducing two correction factors, the prediction accuracy is shown to be improved.