Determination of the best location for setting up a transmission tower in the city

摘要

Mobile phones plays a vital role in humans’ life due to day by day growth in the mobile industry. The cost of deploying, managing, and maintaining the network infrastructure is high. For a large area deployment of a transmission tower at the best location to maintain adequate signal strength is a challenge. Signal strength is measured in terms of -dBm. Importantly, the best location becomes a function of the position of buildings, terrain points, ground points in 3D. So, it is required to determine the paths through which the signal can transmit before reaching the user locations. While propagating from a transmission tower, a signal can directly reach to the user. It can also reach indirectly after diffracting around the buildings or reflecting from the ground and wall. The path detail controls the attenuation of signals and is required to be determined. In this paper, an attempt has been made to find the best location of the transmission tower. Determination of best location required terrain data in 3D. In this work, a LiDAR-based technique is attempted using the point cloud data of RGIPT. The algorithm extracts building, ground, tree, etc. using LiDAR data. Then boundary or edges inside them coming in the path between potential transmission tower to the user are tried to be determined. To find the strength of the signal for the desired user location, the algorithm tried to determine all the buildings and obstructions and their edges to determine the paths of transmission of signals. Once the detailed signal path information is obtained, the terrain parameters (distance, difference, reflection contribution, ground absorption, etc.) are determined. These are then utilized to model the signal strength for any user location. The approach is extended to determine the best location of transmission tower for the RGIPT campus. The technique is generic, novel and can be applied for any terrain condition with the incorporation of the Digital Elevation Model.