Channel, phase noise, and frequency offset in OFDM systems: Joint estimation, data detection, and hybrid Cramér-Rao lower bound

Omar Hazim Salim*, Ali A. Nasir, Hani Mehrpouyan, Wei Xiang, Salman Durrani, Rodney A. Kennedy

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

68 Scopus citations

Abstract

Oscillator phase noise (PHN) and carrier frequency offset (CFO) can adversely impact the performance of orthogonal frequency division multiplexing (OFDM) systems, since they can result in inter carrier interference and rotation of the signal constellation. In this paper, we propose an expectation conditional maximization (ECM) based algorithm for joint estimation of channel, PHN, and CFO in OFDM systems. We present the signal model for the estimation problem and derive the hybrid Cramér-Rao lower bound (HCRB) for the joint estimation problem. Next, we propose an iterative receiver based on an extended Kalman filter for joint data detection and PHN tracking. Numerical results show that, compared to existing algorithms, the performance of the proposed ECM-based estimator is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high signal-to-noise ratio (SNR). In addition, the combined estimation algorithm and iterative receiver are more computationally efficient than existing algorithms and result in improved average uncoded and coded bit error rate (BER) performance.

Original languageEnglish
Article number6868950
Pages (from-to)3311-3325
Number of pages15
JournalIEEE Transactions on Communications
Volume62
Issue number9
DOIs
StatePublished - 1 Sep 2014
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Bayesian
  • Kalman filter
  • OFDM
  • channel estimation
  • data detection
  • frequency offset
  • hybrid Cramér-Rao lower bound
  • phase noise

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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