In this paper we address the sensor localization problem in large-scale wireless sensor networks (WSNs) by using the received signal strength (RSS) measurements. Finding the maximum likelihood (ML) estimate involves solving a non-convex optimization problem, thus making the search for the globally optimal solution hard. Based on the second-order cone programming (SOCP) relaxation, two methods which solve the localization problem in a completely distributed manner are proposed. Computer simulations show that the proposed approaches work well in various scenarios, and efficiently solve the localization problem.
|Title of host publication||Computing, Networking and Communications (ICNC), 2014 International Conference on|
|Pages||853 - 857|
|Publication status||Published - 1 Jan 2014|
|Event||International Conference on Computing, Networking and Communications (ICNC), 2014 - |
Duration: 1 Jan 2014 → …
|Conference||International Conference on Computing, Networking and Communications (ICNC), 2014|
|Period||1/01/14 → …|