Iterative carrier-frequency offset estimation for generalized OFDMA uplink transmission
Maximum likelihood (ML) carrier-frequency offset (CFO) estimation for orthogonal frequency-division multiple-access (OFDMA) uplink with generalized carrier-assignment scheme (GCAS) is a complex multi-parameter estimation problem. The computational complexity of ML solution based on a multi-dimension...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on wireless communications 2009-03, Vol.8 (3), p.1373-1383 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Maximum likelihood (ML) carrier-frequency offset (CFO) estimation for orthogonal frequency-division multiple-access (OFDMA) uplink with generalized carrier-assignment scheme (GCAS) is a complex multi-parameter estimation problem. The computational complexity of ML solution based on a multi-dimensional exhaustive search is prohibitive. The existing sub-optimal solutions reduce the complexity by replacing the multi-dimensional search with a sequence of single-dimensional searches. However, these solutions suffer from either poor estimation accuracy or being still of fairly high complexity. In this paper, we propose a new approach called divide-and-update frequency estimator (DUFE), for CFO estimation. Compared with the existing approaches, the proposed DUFE has lower computational complexity while maintaining high estimation accuracy similar to that of the exact ML solution. Performance and complexity comparisons are provided, along with numerical results to illustrate the effectiveness of the proposed method. |
---|---|
ISSN: | 1536-1276 1558-2248 |
DOI: | 10.1109/TWC.2009.080028 |