2nd International ICST Conference on Mobile Multimedia Communications

Research Article

The effect of narrowband interference on ML fractional frequency offset estimator for OFDM

  • @INPROCEEDINGS{10.1145/1374296.1374353,
        author={Mohamed Marey and Heidi Steendam},
        title={The effect of narrowband interference on ML fractional frequency offset estimator for OFDM},
        proceedings={2nd International ICST Conference on Mobile Multimedia Communications},
        publisher={ACM},
        proceedings_a={MOBIMEDIA},
        year={2006},
        month={9},
        keywords={},
        doi={10.1145/1374296.1374353}
    }
    
  • Mohamed Marey
    Heidi Steendam
    Year: 2006
    The effect of narrowband interference on ML fractional frequency offset estimator for OFDM
    MOBIMEDIA
    ACM
    DOI: 10.1145/1374296.1374353
Mohamed Marey1,*, Heidi Steendam1,*
  • 1: Ghent University, Gent, BELGIUM
*Contact email: mohamed@telin.ugent.be, hs@telin.ugent.be

Abstract

In orthogonal frequency division multiplexing (OFDM) systems affected by carrier frequency offsets, the estimation of the frequency offset corresponding to a fractional part of the carrier spacing is a crucial issue. The proper action of the fractional frequency estimator can be strongly affected by the presence of disturbances, like narrowband interference (NBI) signals. In this paper, we derive the data-aided maximum-likelihood (ML) fractional frequency estimator in the presence of (NBI). Based on the ML algorithm which has a high complexity, we propose a number of simplifications to develop a lower complexity algorithm. The susceptibility of the simplified fractional frequency estimator to NBI signals is investigated in an analytical way. The analytical results are verified by means of simulations. Although the simplified estimator turns out to be essentially independent of the bandwidth and the location of interferers, the performance of the estimator is very sensitive to the signal to interference ratio and the number of interferers. In contrast with the simplified estimator, simulation results indicate that the exact ML estimator is essentially independent of the (NBI) signals.