Power adaptation for vector parameter estimation according to Fisher information based optimality criteria

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Gurgunoglu D., DÜLEK B., GEZİCİ S.

SIGNAL PROCESSING, vol.192, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 192
  • Publication Date: 2022
  • Doi Number: 10.1016/j.sigpro.2021.108390
  • Journal Name: SIGNAL PROCESSING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, zbMATH
  • Keywords: Cramer-Rao lower bound, Estimation, Fisher information, Power adaptation, RANGING ENERGY OPTIMIZATION, ALLOCATION, LOCALIZATION
  • Hacettepe University Affiliated: Yes

Abstract

The optimal power adaptation problem is investigated for vector parameter estimation according to various Fisher information based optimality criteria. By considering an observation model that involves a linear transformation of the parameter vector and an additive noise component with an arbitrary probability distribution, six different optimal power allocation problems are formulated based on Fisher information based objective functions. Via optimization theoretic approaches, various closed-form solutions are derived for the proposed problems. Also, the results are extended to cases in which nuisance parameters exist in the system model or certain types of nonlinear transformations are applied on the parameter vector. Numerical examples are presented to investigate performance of the proposed power allocation strategies. (C) 2021 Elsevier B.V. All rights reserved.