Coverage Probability Analysis of WiMAX Network under Additive White Gaussian Noise and Predicted Empirical Path Loss Model

Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

Abstract:

This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.2702873

References:

[1] T. S. Rappaport, Wireless Communication: principles and practice., 2nd ed. New Jersey: Prentice Hall PTR, 1996.
[2] J. F. Aguirre; F. Magnago, “Viability of WiMAX for Smart Grid Distribution Network,” Eur. Int. J. Sci. Technol., vol. 2, no. 3, pp. 181–196, 2013.
[3] A. Munir, P. Kansakar, and S. U. Khan, “IFCIoT: Integrated Fog Cloud IoT: A novel architectural paradigm for the future Internet of Things,” IEEE Consum. Electron. Mag., vol. 6, no. 3, pp. 74–82, 2017.
[4] H. K. Rath, S. Verma, A. Simha, and A. Karandikar, “Path Loss Model for Indian Terrain - Empirical Approach,” Twenty Second Natl. Conf. Commun. (NCC), Guwahati, pp. 1–6, 2016.
[5] E. T. Tchao, K. Diawuo, and W. K. Ofosu, “Mobile Telemedicine Implementation with WiMAX Technology: A Case Study of Ghana,” J. Med. Syst., vol. 41, no. 1, 2017.
[6] F. Aalamifar and L. Lampe, “Optimized WiMAX Profile Configuration for Smart Grid Communications,” IEEE Trans. Smart Grid, vol. 8, no. 6, pp. 2723–2732, 2017.
[7] D. De Luca, F. Fiano, F. Mazzenga, C. Monti, S. Ridolfi, and F. Vallone, “Outdoor path loss models for IEEE 802.16 in suburban and campus-like environments,” IEEE Int. Conf. Commun. Glas., pp. 4902–4906, 2007.
[8] J. Milanovic, S. Rimac-Drlje, and K. Bejuk, “Comparison of Propagation Models Accuracy for WiMAX on 3.5 GHz,” 14th IEEE Int. Conf. Electron. Circuits Syst. Morocco, pp. 111–114, 2007.
[9] J. Joe et al., “Path loss measurements in sea port for WiMAX,” IEEE Wirel. Commun. Netw. Conf. WCNC, Kowloon, pp. 1873–1878, 2007.
[10] S.-E. Mar, J., Ko, C.-C., Li, C.-H. & Chen, “Cell Planning and Channel Throughput of Mobile WiMAX at 2.5 GHz,” J. Chinese Inst. Eng. 32(5), vol. 32, no. 5, pp. pp.585–97, 2009.
[11] K. L. Chee and T. Kürner, “Effect of terrain irregularities and clutter distribution on wave propagation at 3.5 GHz in suburban area,” Proc. Fourth Eur. Conf. Antennas Propagation, Barcelona, pp. 1–5, 2010.
[12] D. Urban, C. Dalela, M. V. S. N. Prasad, P. K. Dalela, and R. Saraf, “Analysis of WiMAX Radio Measurements and Comparison With Some Models Over,” IEEE Antennas Wirel. Propag. Lett., vol. 10, pp. 730–733, 2011.
[13] B. T. Ahmed, J. L. M. Campos, and J. M. L. Mayordomo, “Propagation path loss and materials insertion loss in indoor environment at WiMAX band of 3.3 to 3.6 GHz,” Wirel. Pers. Commun., vol. 66, no. 2, pp. 251–260, 2012.
[14] S. Sharma and B. Singh, “Experimental study of a fixed WiMAX network at 2.62 GHz,” Wirel. Pers. Commun., vol. 72, no. 4, pp. 2127–2141, 2013.
[15] B. Singh and S. Sharma, “Optimising capacity–coverage of a fixed WiMAX network,” IET Microwaves, Antennas Propag., vol. 8, no. 10, pp. 708–713, 2014.