Channel, Phase Noise, and Frequency Offset in OFDM Systems: Joint Estimation, Data Detection, and Hybrid Cramer-Rao Lower Bound

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 Cramer-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

Channel estimation, data detection and carrier frequency offset estimation in OFDM systems

Orthogonal Frequency Division Multiplexing (OFDM) plays an important role in the implementation of high data rate communication. In this thesis, the problems of data detection and channel and carrier frequency offset estimation in OFDM systems are studied. Multi-symbol non-coherent data detection is studied which performs data detection by processing multiple symbols without the knowledge of the channel impulse response (CIR). For coherent data detection, the CIR needs to be estimated. Our objective in this thesis is to work on blind channel estimators which can extract the CIR using just one block of received OFDM data. A blind channel estimator for (Single Input Multi Output) SIMO OFDM systems is derived. The conditions under which the estimator is identifiable is studied and solutions to resolve the phase ambiguity of the proposed estimator are given.A channel estimator for superimposed OFDM systems is proposed and its CRB is derived. The idea of simultaneous transmission of pilot and data symbols on each subcarrier, the so called superimposed technique, introduces the efficient use of bandwidth in OFDM context. Pilot symbols can be added to data symbols to enable CIR estimation without sacrificing the data rate. Despite the many advantages of OFDM, it suffers from sensitivity to carrier frequency offset (CFO). CFO destroys the orthogonality between the subcarriers. Thus, it is necessary for the receiver to estimate and compensate for the frequency offset. Several high accuracy estimators are derived. These include CFO estimators, as well as a joint iterative channel/CFO estimator/data detector for superimposed OFDM. The objective is to achieve CFO estimation with using just one OFDM block of received data and without the knowledge of CIR

Optimal OFDM channel estimation with carrier frequency offset and phase noise

Abstract-We propose an optimal training-based OFDM channel impulse response (CIR) estimation algorithm that addresses the phase noise (PHN) and carrier frequency offset (CFO) problem. If left unattended, these combined problems severely degrade the accuracy of the channel estimate and ultimately the quality of the wireless link. The solution involves the joint optimization of a complete log-likelihood function over the unknown CIR, PHN and CFO. To reduce the complexity of the proposed algorithm, a simplification based on the conjugate gradient method is introduced, yielding an efficient realization using the Fast Fourier Transform (FFT) with only minor performance degradation