206 Int. J. Wireless and Mobile Computing, Vol. 8, No. 2, 2015 Copyright © 2015 Inderscience Enterprises Ltd. An empirical investigation of RSSI-based distance estimation for wireless indoor positioning system Nazrul M. Ahmad* and Anang Hudaya Muhamad Amin Thundercloud Research Laboratory, Faculty of Information Science & Technology (FIST), Multimedia University (MMU), Jalan Ayer Keroh Lama, 75450 Melaka, Malaysia Email: nazrul.muhaimin@mmu.edu.my Email: anang.amin@mmu.edu.my *Corresponding Author Mohd Faizal Abdollah and Robiah Yusof Faculty of Information and Communication Technology (FTMK), University Teknikal Malaysia Melaka (UTeM), 76100 Durian Tunggal, Melaka, Malaysia Email: faizalabdollah@utem.edu.my Email: robiah@utem.edu.my Abstract: RSSI-based distance estimation techniques for wireless indoor positioning system require extensive offline calibration to construct propagation model in order to describe the relationship between received signal strength and distance. This paper investigates the accuracy of the well-known propagation models against the measured data at indoor building. From the results, the dual slope model exhibits the best propagation model and it is chosen as the reference for further investigation. The accuracy of dual slope model in distance estimation suffers from the degradation due to the presence of Non Line of Sight (NLOS) condition between mobile station and access point. Therefore, to further improve the accuracy, this paper studies the effect of breakpoint distance and evaluates two simple techniques, running variance and kurtosis index, to identify the NLOS condition. Once the NLOS condition is identified, the best dual slope model can be selected for accurate distance estimation. Keywords: indoor positioning; distance estimation; dual slope propagation model; NLOS identification; wireless network. Reference to this paper should be made as follows: Ahmad, N.M., Amin, A.H.M., Abdollah, M.F. and Yusof, R. (2015) ‘An empirical investigation of RSSI-based distance estimation for wireless indoor positioning system’, Int. J. Wireless and Mobile Computing, Vol. 8, No. 2, pp.206–212. Biographical notes: Nazrul M. Ahmad is a Lecturer in the Faculty of Information Science and Technology (FIST), Multimedia University (MMU), Malaysia. He is currently pursuing his PhD degree in the Faculty of Information and Communication Technology, University Technical Malaysia Melaka (UTeM). He received a BEng (Hons) in Electronics with Communication Engineering from University of York, UK and the MSc in Information Technology from Multimedia University (MMU). His research interests include wireless communication and security and cloud computing. Mohd Faizal Abdollah is currently working as a Senior Lecturer in Department of Computer and Communication System, Faculty of Information and Communication Technology, University Technical Malaysia Melaka (UTeM). He received his first degree and Master degree from University Utara Malaysia and University Kebangsaan Malaysia. He obtained his PhD from University Technical Malaysia Melaka in Computer and Network Security. Previously, he worked as a MIS Executive at EON Berhad, Selangor and as a System Engineer in Multimedia University, Melaka for six years. His interest is mainly in network and wireless technology, network management and network and wireless security. Robiah Yusof is currently a Senior Lecturer in the Universiti Teknikal Malaysia Melaka (UTeM). She received the BSc (Hons) of Computer Studies and Master of Information Technology from Liverpool John Moore’s University, UK and Universiti Kebangsaan Malaysia, respectively. She obtained the Doctor of Philosophy, Network Security from Universiti Teknikal Malaysia Melaka (UTeM). Her research interests include network security, computer system security, network administration, network management and network design.