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Data-Aided Autoregressive Sparse Channel Tracking for OFDM Systems

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Date
2016
Author
Buyuksar, Ayse Betul
Şenol, Habib
Erküçük, Serhat
Cirpan, Hakan Ali
Abstract
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.

Source

2016 13th International Symposium on Wireless Communication Systems (ISWCS)

Pages

424-428

URI

https://hdl.handle.net/20.500.12469/529
https://doi.org/10.1109/ISWCS.2016.7600941

Collections

  • Araştırma Çıktıları / Scopus [1565]
  • Araştırma Çıktıları / WOS [1518]
  • Bilgisayar Mühendisliği / Computer Engineering [188]
  • Elektrik-Elektronik Mühendisliği / Electrical - Electronics Engineering [321]

Keywords

OFDM
Autoregressive Model
Fast Time-Varying
Sage-Map
OMP
Sparse Channel Estimation

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