TY - GEN
T1 - Hybrid RSS-based fingerprinting positioning method with segmentation and KNN in cellular network
AU - Abdelghani, Belaabed
AU - Qiang, Gao
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/26
Y1 - 2017/10/26
N2 - Positioning method based on Receive Signal Strength (RSS) is one of the outdoor positioning methods that have a wide range of applications in wireless communication networks. Thus, the main purpose of this paper is to investigate RSS fingerprint-based positioning in cellular wireless networks. In this work, we propose a hybrid algorithm that integrates KNearest Neighbor (KNN) location-based fingerprint approach with fingerprint location estimation based on segmentation approach to improve the positioning accuracy. The performance of the proposed method was evaluated by data that are collected in a dense urban environment. The experimental tests discussed in this paper show that the proposed segmentation-based fingerprinting method provides satisfactory results of localization in an urban environment.
AB - Positioning method based on Receive Signal Strength (RSS) is one of the outdoor positioning methods that have a wide range of applications in wireless communication networks. Thus, the main purpose of this paper is to investigate RSS fingerprint-based positioning in cellular wireless networks. In this work, we propose a hybrid algorithm that integrates KNearest Neighbor (KNN) location-based fingerprint approach with fingerprint location estimation based on segmentation approach to improve the positioning accuracy. The performance of the proposed method was evaluated by data that are collected in a dense urban environment. The experimental tests discussed in this paper show that the proposed segmentation-based fingerprinting method provides satisfactory results of localization in an urban environment.
KW - adaptive threshold
KW - connected component labeling
KW - fingerprinting positioning
KW - received signal strength
KW - segmentation
UR - https://www.scopus.com/pages/publications/85040107763
U2 - 10.1109/CCSSE.2017.8088042
DO - 10.1109/CCSSE.2017.8088042
M3 - 会议稿件
AN - SCOPUS:85040107763
T3 - 2017 3rd IEEE International Conference on Control Science and Systems Engineering, ICCSSE 2017
SP - 465
EP - 469
BT - 2017 3rd IEEE International Conference on Control Science and Systems Engineering, ICCSSE 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Conference on Control Science and Systems Engineering, ICCSSE 2017
Y2 - 17 August 2017 through 19 August 2017
ER -