RSS Localization Using Unknown Statistical Path Loss Exponent Model

Due to low complexity, received signal strength source localization in wireless sensor network has gained upsurge of interests in recent years. In this letter, we consider the path loss exponent (PLE) as a random variable in the lognormal shadowing model. Assuming a general distribution function for the PLE, the nonlinear equation for finding the maximum likelihood (ML) distance estimator has been derived. Then, an approximated closed-form formula for the ML distance estimator is derived for uniform distribution of the PLE. Moreover, a Bayesian minimum mean square error estimator has been calculated for the PLE. Finally, localization is performed by a classical linear least square approach. Simulation results show the efficacy of the proposed algorithm in comparison with other methods.