A preprocessing dependent image theory based ray tracing algorithm for indoor coverage solution

Hot spot coverage requirements of indoor environments necessitate adequate network platforms and optimal network planning. Optimal network planning imposes numerous iterative computations and evaluations of network coverage until the best antenna layout is achieved. Therefore, accurate and scalable indoor propagation models become of the ultimate essence. In this paper, image theory adopting a feasible reflection region concept is significantly enhanced using a pre-processing approach. The proposed method stores each mirrored image location, the corresponding feasible reflection region boundaries and the angles between walls of the indoor environment. Received power is calculated using stored data significantly reducing computational complexity in terms of the number of wall intersection tests that are necessary for coverage computations. The preprocessing approach is tested in different indoor configurations with multiple antennas. Simulation results confirm the superior accuracy of the proposed approach as well as the major complexity gain attained relative to other image theory based approaches.