@InProceedings{8553550,
  author = {A. Ladaycia and K. Abed-Meraiml and A. Mokraoui and A. Belouchrani},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Efficient Semi-Blind Subspace Channel Estimation for MIMO-OFDM System},
  year = {2018},
  pages = {1282-1286},
  abstract = {This paper deals with channel estimation for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) wireless communications systems. Herein, we propose a semi-blind (SB) subspace channel estimation technique for which an identifiability result is first established for the subspace based criterion. Our algorithm adopts the MIMO-OFDM system model without cyclic prefix and takes advantage of the circulant property of the channel matrix to achieve lower computational complexity and to accelerate the algorithm's convergence by generating a group of sub vectors from each received OFDM symbol. Then, through simulations, we show that the proposed method leads to a significant performance gain as compared to the existing SB subspace methods as well as to the classical last-squares channel estimator.},
  keywords = {channel estimation;computational complexity;MIMO communication;OFDM modulation;multiple-input multiple-output orthogonal frequency division multiplexing wireless communications systems;last-squares channel estimator;SB subspace methods;channel matrix;MIMO-OFDM system model;subspace based criterion;semiblind subspace channel estimation technique;Channel estimation;OFDM;Estimation;Covariance matrices;Matrix decomposition;Europe;Signal processing},
  doi = {10.23919/EUSIPCO.2018.8553550},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570437248.pdf},
}

{"_id":"wjn3ccS2DgmjaPRaL","bibbaseid":"ladaycia-abedmeraiml-mokraoui-belouchrani-efficientsemiblindsubspacechannelestimationformimoofdmsystem-2018","authorIDs":[],"author_short":["Ladaycia, A.","Abed-Meraiml, K.","Mokraoui, A.","Belouchrani, A."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["A."],"propositions":[],"lastnames":["Ladaycia"],"suffixes":[]},{"firstnames":["K."],"propositions":[],"lastnames":["Abed-Meraiml"],"suffixes":[]},{"firstnames":["A."],"propositions":[],"lastnames":["Mokraoui"],"suffixes":[]},{"firstnames":["A."],"propositions":[],"lastnames":["Belouchrani"],"suffixes":[]}],"booktitle":"2018 26th European Signal Processing Conference (EUSIPCO)","title":"Efficient Semi-Blind Subspace Channel Estimation for MIMO-OFDM System","year":"2018","pages":"1282-1286","abstract":"This paper deals with channel estimation for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) wireless communications systems. Herein, we propose a semi-blind (SB) subspace channel estimation technique for which an identifiability result is first established for the subspace based criterion. Our algorithm adopts the MIMO-OFDM system model without cyclic prefix and takes advantage of the circulant property of the channel matrix to achieve lower computational complexity and to accelerate the algorithm's convergence by generating a group of sub vectors from each received OFDM symbol. Then, through simulations, we show that the proposed method leads to a significant performance gain as compared to the existing SB subspace methods as well as to the classical last-squares channel estimator.","keywords":"channel estimation;computational complexity;MIMO communication;OFDM modulation;multiple-input multiple-output orthogonal frequency division multiplexing wireless communications systems;last-squares channel estimator;SB subspace methods;channel matrix;MIMO-OFDM system model;subspace based criterion;semiblind subspace channel estimation technique;Channel estimation;OFDM;Estimation;Covariance matrices;Matrix decomposition;Europe;Signal processing","doi":"10.23919/EUSIPCO.2018.8553550","issn":"2076-1465","month":"Sep.","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570437248.pdf","bibtex":"@InProceedings{8553550,\n author = {A. Ladaycia and K. Abed-Meraiml and A. Mokraoui and A. Belouchrani},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Efficient Semi-Blind Subspace Channel Estimation for MIMO-OFDM System},\n year = {2018},\n pages = {1282-1286},\n abstract = {This paper deals with channel estimation for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) wireless communications systems. Herein, we propose a semi-blind (SB) subspace channel estimation technique for which an identifiability result is first established for the subspace based criterion. Our algorithm adopts the MIMO-OFDM system model without cyclic prefix and takes advantage of the circulant property of the channel matrix to achieve lower computational complexity and to accelerate the algorithm's convergence by generating a group of sub vectors from each received OFDM symbol. Then, through simulations, we show that the proposed method leads to a significant performance gain as compared to the existing SB subspace methods as well as to the classical last-squares channel estimator.},\n keywords = {channel estimation;computational complexity;MIMO communication;OFDM modulation;multiple-input multiple-output orthogonal frequency division multiplexing wireless communications systems;last-squares channel estimator;SB subspace methods;channel matrix;MIMO-OFDM system model;subspace based criterion;semiblind subspace channel estimation technique;Channel estimation;OFDM;Estimation;Covariance matrices;Matrix decomposition;Europe;Signal processing},\n doi = {10.23919/EUSIPCO.2018.8553550},\n issn = {2076-1465},\n month = {Sep.},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570437248.pdf},\n}\n\n","author_short":["Ladaycia, A.","Abed-Meraiml, K.","Mokraoui, A.","Belouchrani, A."],"key":"8553550","id":"8553550","bibbaseid":"ladaycia-abedmeraiml-mokraoui-belouchrani-efficientsemiblindsubspacechannelestimationformimoofdmsystem-2018","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570437248.pdf"},"keyword":["channel estimation;computational complexity;MIMO communication;OFDM modulation;multiple-input multiple-output orthogonal frequency division multiplexing wireless communications systems;last-squares channel estimator;SB subspace methods;channel matrix;MIMO-OFDM system model;subspace based criterion;semiblind subspace channel estimation technique;Channel estimation;OFDM;Estimation;Covariance matrices;Matrix decomposition;Europe;Signal processing"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2018url.bib","creationDate":"2021-02-13T15:38:40.480Z","downloads":0,"keywords":["channel estimation;computational complexity;mimo communication;ofdm modulation;multiple-input multiple-output orthogonal frequency division multiplexing wireless communications systems;last-squares channel estimator;sb subspace methods;channel matrix;mimo-ofdm system model;subspace based criterion;semiblind subspace channel estimation technique;channel estimation;ofdm;estimation;covariance matrices;matrix decomposition;europe;signal processing"],"search_terms":["efficient","semi","blind","subspace","channel","estimation","mimo","ofdm","system","ladaycia","abed-meraiml","mokraoui","belouchrani"],"title":"Efficient Semi-Blind Subspace Channel Estimation for MIMO-OFDM System","year":2018,"dataSources":["yiZioZximP7hphDpY","iuBeKSmaES2fHcEE9"]}