Now showing items 1-5 of 5

    • Heterogeneous and Opportunistic Wireless Networks 

      Pérez-Romero, J.; Palazzo, S.; Galluccio, L.; Morabito, G.; Leonardi, A.; Antón-Haro, C.; Arikan, E.; Asheid, G.; Belleville, M.; Dagres, I.; Dardari, D.; Dohler, M.; Eldar, Y.; Gezici, Sinan; Giupponi, L.; Guillemot, C.; Iosifidis, G.; Kieffer, M.; Kountouris, M.; Luise, M.; Masera, G.; Matamoros, J.; Miliou, N.; Morche, D.; Moy, C.; Navarro, C.; Olmo, G.; Palicot, J.; Pedone, R.; Ramakrishnan, V.; Shamai, S.; Tyczka, P.; Vandendorpe, L.; Vanelli-Coralli, A.; Weidmann, C.; Zalonis, A. (Springer-Verlag Italia s.r.l., 2012)
      Recent years have witnessed the evolution of a large plethora of wireless technologies with different characteristics, as a response of the operators' and users' needs in terms of an efficient and ubiquitous delivery of ...
    • Statistics of the MLE and Approximate Upper and Lower Bounds-Part 1: Application to TOA Estimation 

      Mallat, A.; Gezici, Sinan; Dardari, D.; Craeye, C.; Vandendorpe, L. (IEEE, 2014-08)
      In nonlinear deterministic parameter estimation, the maximum likelihood estimator (MLE) is unable to attain the Cramer-Rao lower bound at low and medium signal-to-noise ratios (SNR) due the threshold and ambiguity ...
    • Statistics of the MLE and Approximate Upper and Lower Bounds-Part 2: Threshold Computation and Optimal Signal Design 

      Mallat, A.; Gezici, Sinan; Dardari, D.; Vandendorpe, L. (, 2014)
      Threshold and ambiguity phenomena are studied in Part I of this paper where approximations for the mean-squared error (MSE) of the maximum-likelihood estimator are proposed using the method of interval estimation (MIE), ...
    • Statistics of the MLE and approximate upper and lower bounds-Part I: Application to TOA estimation 

      Mallat, A.; Gezici, Sinan; Dardari, D.; Craeye, C.; Vandendorpe, L. (Institute of Electrical and Electronics Engineers Inc., 2014)
      In nonlinear deterministic parameter estimation, the maximum likelihood estimator (MLE) is unable to attain the Cramér-Rao lower bound at low and medium signal-to-noise ratios (SNRs) due the threshold and ambiguity phenomena. ...
    • Statistics of the MLE and approximate upper and lower bounds-part II: Threshold computation and optimal pulse design for TOA estimation 

      Mallat, A.; Gezici, Sinan; Dardari, D.; Vandendorpe, L. (Institute of Electrical and Electronics Engineers Inc., 2014)
      Threshold and ambiguity phenomena are studied in Part I of this paper where approximations for the mean-squared error (MSE) of the maximum-likelihood estimator are proposed using the method of interval estimation (MIE), ...