Data-aided autoregressive sparse channel tracking for OFDM systems

Ayse Betul Buyuksar, Habib Senol, Serhat Erkucuk, Hakan Ali Cirpan

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

2 Atıf (Scopus)

Özet

In order to meet future communication system requirements, channel estimation over fast fading and frequency selective channels is crucial. In this paper, Space Alternated Generalized Expectation Maximization Maximum a Posteriori (SAGE-MAP) based channel estimation algorithm is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems for Autoregressive (AR) modeled time-varying sparse channels. Also, an initialization algorithm has been developed from the widely used sparse approximation algorithm Orthogonal Matching Pursuit (OMP), since the performance of SAGE algorithm strictly depends on initialization. The results show that multipath delay positions can be tracked successfully for every time instant using the proposed SAGE-MAP based approach.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıISWCS 2016 - 13th International Symposium on Wireless Communication Systems, Proceedings
YayınlayanVDE Verlag GmbH
Sayfalar424-428
Sayfa sayısı5
ISBN (Elektronik)9781509020614
DOI'lar
Yayın durumuYayınlandı - 19 Eki 2016
Etkinlik13th International Symposium on Wireless Communication Systems, ISWCS 2016 - Poznan, Poland
Süre: 20 Eyl 201623 Eyl 2016

Yayın serisi

AdıProceedings of the International Symposium on Wireless Communication Systems
Hacim2016-October
ISSN (Basılı)2154-0217
ISSN (Elektronik)2154-0225

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Ülke/BölgePoland
ŞehirPoznan
Periyot20/09/1623/09/16

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

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