Estimating DoA From Radio Frequency RSSI Measurements Using Multi-Element Femtocell Configuration

In this paper, a method to estimate the direction of arrival (DoA) of a radio signal using a multi-element antenna based femtocell device is presented. The femtocell estimates the DoA by identifying the peak of received signal strength indicator (RSSI) measurement using multi-element microstrip antenna. This paper is a modified version of a previously reported work titled as estimation of DoA from radio frequency RSSI measurements using an actuator reflector. In long term evaluation, ultradense deployment of the femtocell device is mainly supported by the intelligent beam forming that translates directly to the constraint of DoA estimation. Use of multi-element antenna over omnidirectional antenna in femtocell is mandated by coverage optimization and reduction of cell overshooting. DoA estimation using microstrip antenna alone is a challenging problem, but it is easier with a multiple number of directive antennas covering the whole plane. Other DoA estimation methods, such as phase arrays, are unsuitable for a small device like femtocell due to the complexity and cost limitations. The proposed method to estimate the DoA is simple enough to be applicable for femtocell indoor applications. Both simulation and experimental results are analyzed to evaluate the performance of the method. Results show that the error in estimated DoA has a mean <;7° and standard deviation <;4°.

[1]  Mahamod Ismail,et al.  A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network , 2014, TheScientificWorldJournal.

[2]  Thomas Bernoulli,et al.  Semi-autonomous indoor positioning using MEMS-based inertial measurement units and building information , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[3]  Hao Guo,et al.  Optimizing the Localization of a Wireless Sensor Network in Real Time Based on a Low-Cost Microcontroller , 2011, IEEE Transactions on Industrial Electronics.

[4]  Ada Vittoria Bosisio Performances of an RSSI-based positioning and tracking algorithm , 2011, 2011 International Conference on Indoor Positioning and Indoor Navigation.

[5]  R. Weigel,et al.  GSM mobile phone localization using time difference of arrival and angle of arrival estimation , 2012, International Multi-Conference on Systems, Sygnals & Devices.

[6]  B N Hood,et al.  Estimating DoA From Radio-Frequency RSSI Measurements Using an Actuated Reflector , 2011, IEEE Sensors Journal.

[7]  Liu Ke-zhong,et al.  An Improved DV-Hop Localization Algorithm for Wireless Sensor Networks , 2006 .

[8]  Holger Claussen,et al.  Femtocell Coverage Optimization Using Switched Multi-Element Antennas , 2009, 2009 IEEE International Conference on Communications.

[9]  Chang-Fa Yang,et al.  A ray tracing method for modeling indoor wave propagation and penetration , 1996 .

[10]  Mahamod Ismail,et al.  A Review on Femtocell and its Diverse Interference Mitigation Techniques in Heterogeneous Network , 2014, Wireless Personal Communications.

[11]  Andreas Fink,et al.  Analysis of RSS-based location estimation techniques in fading environments , 2011, 2011 International Conference on Indoor Positioning and Indoor Navigation.

[12]  Xiao Zheng,et al.  Radio Characterization of 802.15.4 and Its Impact on the Design of Mobile Sensor Networks , 2008, EWSN.

[13]  Eric A. Wan,et al.  RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers , 2009, IEEE Journal of Selected Topics in Signal Processing.

[14]  Marc Van Droogenbroeck,et al.  A New Three Object Triangulation Algorithm for Mobile Robot Positioning , 2014, IEEE Transactions on Robotics.

[15]  Deborah Estrin,et al.  GPS-less low-cost outdoor localization for very small devices , 2000, IEEE Wirel. Commun..

[16]  Mohammad Tariqul Islam,et al.  Microstrip Antenna Design for Femtocell Coverage Optimization , 2014 .

[17]  C. Balanis Advanced Engineering Electromagnetics , 1989 .

[18]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[19]  Andrei Szabo,et al.  WLAN-Based Pedestrian Tracking Using Particle Filters and Low-Cost MEMS Sensors , 2007, 2007 4th Workshop on Positioning, Navigation and Communication.

[20]  Simo Ali-Löytty,et al.  A comparative survey of WLAN location fingerprinting methods , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.