Communication Data Enhanced Direct Position Determination Under Multipath Environments

We investigate the communication data enhanced direct position determination (DPD) for uplink multi-antenna orthogonal frequency division multiplexing (OFDM) systems. Different from prior related works, both pilot and unknown data signals are employed to estimate the positions of the mobile station (MS) and the virtual points corresponding to non-line-ofsight (NLOS) paths. To solve the novel localization problem, we propose a space alternating generalized expectation maximization (SAGE) based algorithm which regards the unknown data as latent variables. We further analyze the localization CramerRao bound (CRB) that incorporates the impact of communication data. Simulation results and the CRB analysis verify the remarkable localization accuracy improvement achieved by employing data signals. Moreover, the localization performance is also shown to approach the communication data aware CRB under relatively high signal-to-noise ratios (SNRs).