Path loss model development for indoor signal loss prediction at 2.4 GHz 802.11n network

This study focuses on developing an indoor empirical path loss prediction model for 802.11n network at 2.4 GHz. As 802.11n features Multiple-Input Multiple-Output (MIMO) which is not present in any previous wireless local area network (WLAN) standards, it is considered imperative to figure out a suitable prediction model for 802.11n network. Path loss exponent n values were calculated using regression fitting method based on data collected on site. Measurement comparisons between several established prediction models with the actual measurements are taken at an academic building to identify which model gives the best estimation result. The best model produced a mean error of 6.46 dB and would then be further optimized through formula modifications to increase signal prediction accuracy. Prediction results of the optimized model showed that the mean error is reduced to 3.27 dB. Validation of the optimized model has been conducted in a different office building and the prediction results still showed good accuracy, with a mean error of 3.38 dB. This new optimized model is named as Solah's Model and is recommended for predicting indoor signal loss in 802.11n WLAN, especially in assisting network deployment, migration and management.