On the Uniqueness of the Quasi-Moment-Method Solution to the Pathloss Model Calibration Problem

Investigations in this paper focus on establishing the uniqueness properties of Quasi-Moment-Method (QMM) solution to problem calibrating nominal radiowave propagation pathloss prediction models. Nominal (basic) models utilized for investigations, were first subjected QMM calibrations with measurements from three different scenarios. Then, recast forms suitable Singular Value Decomposition (SVD) calibration before being calibrated both SVD and algorithms. The performances as evaluated terms Root Mean Square Prediction Error (RMSE), (MPE), Grey Relational Grade-Mean Absolute Percentage (GRG-MAPE) very clearly indicate that of  QMM-calibrations basic is more readily observable, when are specific calibration. In representative case indoor-to-outdoor measurements, RMSE values recorded QMM-calibrated 5.2639dB ECC33 model, 5.3218dB other Corresponding metrics alternative (rearranged) emerged 5.2663dB model 5.2591dB A similar general trend featured GRG-MAPE metrics, which all models, was 0.9131, but differed slightly (between 0.9138 0.9196) slight differences between these (due computational round-off approximations) confirm  components linearly independent, unique. Planning wireless communications network deployment may consequently select any choice QMM-calibration, hence, identify relative contributions by model’s component parts.