Blind frequency-offset estimator for OFDM systems transmitting constant-modulus symbols

We address the problem of carrier frequency offset (CFO) synchronization in OFDM communications systems in the context of frequency-selective fading channels. We consider the case where the transmitted symbols have constant modulus, i.e., PSK constellations. A novel blind CFO estimation algorithm is developed. The new algorithm is shown to greatly outperform a recently published blind technique that exploits the fact that practical OFDM systems are not fully loaded. Further, the proposed algorithm is consistent even when the system is fully loaded. Finally, the proposed CFO estimator is obtained via a one-dimensional search, the same as with the existing virtual subcarrier-based estimator, but achieves a substantial gain in performance (10-dB SNR or one order of magnitude in CFO MSE)

A time-domain control signal detection technique for OFDM

Transmission of system-critical control information plays a key role in efficient management of limited wireless network resources and successful reception of payload data information. This paper uses an orthogonal frequency division multiplexing (OFDM) architecture to investigate the detection performance of a time-domain approach used to detect deterministic control signalling information. It considers a type of control information chosen from a finite set of information, which is known at both transmitting and receiving wireless terminals. Unlike the maximum likelihood (ML) estimation method, which is often used, the time-domain detection technique requires no channel estimation and no pilots as it uses a form of time-domain correlation as the means of detection. Results show that when compared with the ML method, the time-domain approach improves detection performance even in the presence of synchronisation error caused by carrier frequency offset

Frequency synchronization techniques in wireless communication

In this thesis various iterative channel estimation and data detection techniques for time-varying frequency selective channels with multiple frequency offsets are proposed. Firstly, a maximum likelihood approach for the estimation of complex multipath gains (MGs) and real Doppler shifts (DSs) for a single input "single output (SISO) frequency selective channel is proposed. In a time di vision multiple access (TDMA) system, for example the third-generation global system, or mobile GSM communications, the pilot symbols are generally inadequate to provide enough resolution to estimate frequency offsets. Therefore, our approach is to use the pilot sequence for the estimation and equalization of the channel without consideration to frequency offsets, and then to use the soft estimates of the transmitted signal as a long pilot sequence to determine iteratively the multiple frequency offsets and refine the channel estimates. Inter-symbol interference (ISI) is removed with a linear structure turbo equalizer where the filter coefficients are chosen based on the minimum mean square error (MMSE) criterion. The detection performance is verified using the bit error rate (BER) curves and the frequency offset estimation performance through comparison with appropriate Cramer-Rao lower bounds. This work is then extended for a multi-user transmission system where the channel is modelled as a multi input multi output (MIMO) TDMA system. For the iterative channel estimation, the MIMO frequency selective channel is decoupled into multiple SISO flat fading sub-channels through appropriately cancelling both inter-symbol-interference (ISI) and inter-user-interference (IUI) from the received signal. The refined channel estimates and the corresponding frequency offset estimates are then obtained for each resolved MIMO multipath tap. Simulation results confirm a superior BER and estimation performance. Finally, these iterative equalization and estimation techniques are ex tended to orthogonal frequency division multiplexing (OFDM) based SISO and MIMO systems. For OFDM, the equalization is performed in two stages. In the first stage, the channel and the frequency offsets are estimated in the time domain, while in the second stage, the transmitted symbols are estimated in the frequency domain and the mean values and the variances of the symbols are determined in the frequency domain. These two procedures interact in an iterative manner, exchanging information between the time and frequency domains. Simulation studies show that the proposed iterative scheme has the ability to track frequency off sets and provide a superior BER performance as compared to a scheme that does not track frequency offsets

Frequency synchronization techniques in wireless communication

In this thesis various iterative channel estimation and data detection techniques for time-varying frequency selective channels with multiple frequency offsets are proposed. Firstly, a maximum likelihood approach for the estimation of complex multipath gains (MGs) and real Doppler shifts (DSs) for a single input "single output (SISO) frequency selective channel is proposed. In a time di vision multiple access (TDMA) system, for example the third-generation global system, or mobile GSM communications, the pilot symbols are generally inadequate to provide enough resolution to estimate frequency offsets. Therefore, our approach is to use the pilot sequence for the estimation and equalization of the channel without consideration to frequency offsets, and then to use the soft estimates of the transmitted signal as a long pilot sequence to determine iteratively the multiple frequency offsets and refine the channel estimates. Inter-symbol interference (ISI) is removed with a linear structure turbo equalizer where the filter coefficients are chosen based on the minimum mean square error (MMSE) criterion. The detection performance is verified using the bit error rate (BER) curves and the frequency offset estimation performance through comparison with appropriate Cramer-Rao lower bounds. This work is then extended for a multi-user transmission system where the channel is modelled as a multi input multi output (MIMO) TDMA system. For the iterative channel estimation, the MIMO frequency selective channel is decoupled into multiple SISO flat fading sub-channels through appropriately cancelling both inter-symbol-interference (ISI) and inter-user-interference (IUI) from the received signal. The refined channel estimates and the corresponding frequency offset estimates are then obtained for each resolved MIMO multipath tap. Simulation results confirm a superior BER and estimation performance. Finally, these iterative equalization and estimation techniques are ex tended to orthogonal frequency division multiplexing (OFDM) based SISO and MIMO systems. For OFDM, the equalization is performed in two stages. In the first stage, the channel and the frequency offsets are estimated in the time domain, while in the second stage, the transmitted symbols are estimated in the frequency domain and the mean values and the variances of the symbols are determined in the frequency domain. These two procedures interact in an iterative manner, exchanging information between the time and frequency domains. Simulation studies show that the proposed iterative scheme has the ability to track frequency off sets and provide a superior BER performance as compared to a scheme that does not track frequency offsets.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

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