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—The received signal strength (RSS)-based approach to wireless localization offers the advantage of low cost and easy implementability. To circumvent the nonconvexity of the conventional maximum likelihood (ML) estimator, in this paper, we propose convex estimators specifically for the RSS-based localization problems. Both noncooperative and cooperative(More)
For indoor location estimation based on wireless local area networks fingerprinting, how to reduce the offline calibration effort while maintaining high location estimation accuracy is of major concern. In this paper, a hybrid generative/discriminative semi-supervised learning algorithm is proposed that utilizes a large number of unlabeled samples to(More)
—In a macrodiversity cellular system, switching radio links between base stations cannot be done instantaneously. Thus, branch selection is usually based on the measurement of the slowly varying local-mean power rather than the rapidly varying instantaneous signal power. In this paper, we offer an exact mathematical model to analyze the performance of a(More)