• DocumentCode
    1789726
  • Title

    Iterative LMMSE individual channel estimation with superimposed training over one-way relay networks

  • Author

    Shun Zhang ; Min Sheng ; Feifei Gao

  • Author_Institution
    State Key Lab. of Integrated Service Networks, Xi´dian Univ., Xi´an, China
  • fYear
    2014
  • fDate
    10-14 June 2014
  • Firstpage
    4717
  • Lastpage
    4721
  • Abstract
    In this paper, we investigate the individual channel estimation for three-node one-way relay network (OWRN), where both source and destination are equipped with multiple antennas. Without resorting to the composite channel estimation, as did in the traditional work, we directly estimate the individual channels from an iterative linear minimum mean-square-error (LMMSE) estimator. The closed-form least square (LS) channel estimator is also derived through matrix unitary diagonalization to provide a good initialization for the iterative LMMSE estimator. To make the work more complete, we present two performance lower bounds: Bayesian Cramér lower bound (BCRB) and linear estimation lower bound (LELB), for the proposed algorithm. Numerical results are provided to corroborate our proposed studies.
  • Keywords
    antennas; channel estimation; iterative methods; least mean squares methods; matrix algebra; relay networks (telecommunication); BCRB; Bayesian Cramér lower bound; LELB; LS channel estimation; OWRN; closed-form least square channel estimator; composite channel estimation; iterative LMMSE individual channel estimation; iterative linear minimum mean-square-error estimator; linear estimation lower bound; matrix unitary diagonalization; multiple antennas; superimposed training; three-node one-way relay network; Antennas; Bayes methods; Channel estimation; Estimation; Relays; Signal processing; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2014 IEEE International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/ICC.2014.6884066
  • Filename
    6884066