Variational message passing-based localisation algorithm with Taylor expansion for wireless sensor networks

Variational message passing-based localisation algorithm with Taylor expansion for wireless sensor networks

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

For localisation algorithms of wireless sensor networks (WSNs), the communication overhead and the computational complexity are two main bottlenecks that should be considered beside the positioning accuracy. In this study, the authors focus on cooperative localisation in WSNs and propose a low-complexity distributed cooperative localisation algorithm by employing variational message passing (VMP) on factor graphs. In order to decrease the communication overhead, Gaussian parametric message representation is adopted. With regard to the non-Gaussian messages caused by the non-linear ranging model, they approximate them to Gaussian messages by exploiting second-order Taylor expansion to reduce the computational complexity. Simulation results show that the proposed algorithm performs quite similar to sum-product algorithm over a wireless network and Gaussian VMP algorithm based on minimising Kullback–Leibler divergence with lower computational complexity.


    1. 1)
    2. 2)
    3. 3)
    4. 4)
      • 4. Hofmann-Wellenhof, B., Lichtenegger, H., Collins, J.: ‘Global positioning system: theory and practice’ (Springer-Verlag, Wien, 2001).
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
      • 13. Caceres, M.A., Sottile, F., Garello, R., et al: ‘Hybrid GNSS-ToA localization and tracking via cooperative unscented Kalman filter’. IEEE 21st Int. Symp. on Personal, Indoor and Mobile Radio Communications Workshops (PIMRC Workshops), Istanbul, Turkey, September 2010, pp. 272276.
    14. 14)
      • 14. Sottile, F., Wymeersch, H., Caceres, M.A., et al: ‘Hybrid GNSS-terrestrial cooperative positioning based on particle filter’. IEEE Global Telecommunications Conf. (GLOBECOM), Houston, TX, USA, December 2011, pp. 15.
    15. 15)
    16. 16)
    17. 17)
    18. 18)
      • 18. Lien, J., Ferner, U.J., Srichavengsup, W., et al: ‘A comparison of parametric and sample-based message representation in cooperative localization’, Int. J. Navig. Obs., 2012, p. 10,
    19. 19)
    20. 20)
    21. 21)
      • 21. Wu, N., Li, B., Wang, H., et al: ‘Distributed cooperative localization based on Gaussian message passing on factor graph in wireless networks’, Sci. China Inf. Sci., 2015, 58, (4), pp. 115.
    22. 22)
      • 22. Riegler, E., Kirkelund, G.E., Manchón, C.N., et al: ‘Merging belief propagation and the mean field approximation: a free energy approach’. Int. Symp. on Turbo Codes and Iterative Information Processing (ISTC), Brest, France, September 2010, pp. 256260.
    23. 23)
    24. 24)
      • 24. Pedersen, C., Pedersen, T., Fleury, B.H.: ‘A variational message passing algorithm for sensor self-localization in wireless networks’. IEEE Int. Symp. on Information Theory Proc. (ISIT), St. Petersburg, Russia, August 2011, pp. 21582162.
    25. 25)
      • 25. Rice, S.O.: ‘Mathematical analysis of random noise’ (Bell Telephone Labs Inc., New York, Technical publication, 1944).

Related content

This is a required field
Please enter a valid email address