Proposed Prediction Framework for Improving the Accuracy of Path loss Models of WiMAX Network

Abstract

Worldwide interoperability for Microwave Access (WiMAX) is an advanced wireless broadband access technology for delivering high speed voice, video and multimedia access for fixed as well as mobile users. Planning and deployment of this network is considered as a crucial challenge because it depends upon the accurate estimation of parameters such as link budget, coverage area, capacity, capital expenditure and operational expenditure etc. However, estimation of the above mentioned parameters is substantially relied on accuracy of predicted path loss model between the base station and the receiver. From data analysis theory, it is found that the presence of outliers in data set have notable impact on the correctness of predicted models. Hence, in this paper a prediction framework is proposed which suggests the inclusion of outlier removal algorithm along with data collection, statistical analysis and regression analysis for improving the accuracy of path loss model. Several measurement campaigns are conducted in a WiMAX network deployed in a suburban area for collection of data such as received signal strength indicator (RSSI), and carrier to interference plus noise ratio (CINR). Further, the impact of proposed framework in improving the accuracy of predicted RSSI, CINR and path loss models for the concerned scenario is investigated through simulation based study. Also, the impact of proposed algorithm on probability density function of path loss as well as link budget performance is investigated. From the result analysis, it is observed that the estimated path loss model closes to SUI A path loss model and SUI C path loss model without and with using the proposed approach respectively. Further, the path loss exponents of the predicted path loss models are evaluated as 3.78 and 3.47 without and with utilizing the proposed framework respectively.