Comparison of Various Neural NetworkAlgorithms Used for Location Estimation inWireless Communication

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering

article

G.S. Tripathi¹ 

[1] Dept. of Electronics and Communication Engineering, MMM Engineering College

关键词: Wireless Location;    TOA;    NLOS;    Artificial Neural Network;    RMS error;    LM;    Rprop;    CGP;    CGF.;   

来源: Research & Reviews

【 摘 要 】

In recent years, Artificial Neural Network has been the topic of great interest in the field of Wireless Communication in different ways. To enhance the accuracy of location estimation, we propose the various neural network algorithms i.e. Resilient back-propagation (Rprop), Levenburg-Marquardt (LM), Conjugate gradient with Polak-Ribiere Updates (CGP), Conjugate gradient with Fletcher-Reeves Updates (CGF) utilizing the time of arrival (TOA) measurement information in presence of NLOS error to locate the mobile station (MS) with three base station available. Computer simulations have been performed by using Neural Network Toolbox for MATLAB and then performance of various algorithms has been compared in terms of root mean square (RMS) error.

【 授权许可】

Unknown