In this paper we deal with the problem of data- aided symbol timing estimation for orthogonal frequency division multiplexing systems based on offset-QAM modulation (OFDM/OQAM). Specifically, a data-aided joint phase offset and symbol timing estimator, based on the least squares (LS) approach, exploiting the conjugate-symmetry property of a properly designed training symbol, is derived. Since the phase estimate is in closed form, the symbol timing estimate requires only an one-dimensional maximization procedure. The derived LS estimator does not require the knowledge of the prototype filter and, moreover, its performance, is independent of the carrier frequency offset.

In this paper we consider the problem of data-aided joint symbol timing and carrier-frequency offset (CFO) estimation for filter bank-based multicarrier (FBMC) systems. As all multicarrier systems, FBMC systems are very sensitive to synchronization errors, since CFO and symbol timing errors cause interference between successive symbols and adjacent subcarriers which can lead to a severe performance degradation. Therefore, reliable and accurate synchronization algorithms must be designed for these systems. The approach herein presented is based on the deployment of appropriate training sequences. In particular, we propose a new joint symbol timing and CFO synchronization algorithm based on the least squares approach and exploiting the transmission of a training sequence made up of identical parts. The performance of the derived estimators, assessed by computer simulations, is compared with that of two data-aided synchronization algorithms previously proposed in the literature.

In this paper we consider the problem of blind feedforward carrier-frequency offset (CFO) and symbol timing estimation for orthogonal frequency-division multiplexing systems in multipath channels. At first, a closed-form blind CFO estimator based on the least-squares (LS) approach is derived under the assumption that the start position of the FFT window is within the lock-in interval. Then, this assumption is removed and, a joint CFO and symbol timing LS estimator is obtained. Specifically, the proposed joint LS estimator does not require the knowledge of the channel impulse response and/or the insertion of virtual subcarriers. Computer simulation results show that the proposed estimators can outperform several blind CFO and symbol timing estimators previously proposed in the literature.

We consider the problem of semiblind carrier frequency offset (CFO) estimation for OFDM systems. Specifically, we consider a synchronization scheme based on the insertion of pilot tones in the OFDM block. In this case, if the number of subcarriers is sufficiently large, the received signal vector can be modeled as a complex Gaussian random vector with a nonzero mean. Then, by exploiting the joint probability density function for complex Gaussian random vectors, semi- blind maximum likelihood CFO estimators are derived. The performance of the proposed semiblind algorithms is assessed via computer simulations and compared with that of some blind CFO estimators previously proposed in the literature.

In this letter, the problem of blind symbol-timing estimation with M-ary phase-shift keying (M-PSK) signals is considered. An estimator exploiting the constant modulus (CM) property of M-PSK constellations and the structure of the received signal when the convolution of the transmitter's signaling pulse and the receiver filter satisfies the Nyquist criterion is proposed. Since the derived estimator, termed the CM estimator, requires a maximization with respect to a continuous variable, a closed-form approximate CM (ACM) algorithm, suitable for digital implementation, is proposed. Computer simulation results show that with small excess bandwidth factors, the derived ACM algorithm outperforms previously proposed algorithms at moderate and high signal-to-noise ratios

In this paper we investigate the problem of blind carrier frequency offset (CFO) estimation in orthogonal frequency division multiplexing systems based on offset QAM. Specifically, by modeling the received signal as a complex Gaussian random vector and under the hypothesis of a non dispersive channel, we derive the unconditional maximum likelihood CFO estimator. Moreover, due to its computational complexity we consider, successively, the more feasible best linear unbiased estimator. The performance of the proposed algorithms is assessed via computer simulation and compared with that of recently proposed CFO estimators exploiting second order cyclostationarity

In this letter, the cyclostationarity properties of a general class of long-code direct-sequence spread-spectrum (DS-SS) signals are analyzed, and it is shown that these properties can be exploited in long-code DS code-division multiple-access systems. Specifically, it is shown that a continuous-time DS-SS signal exhibits cyclostationarity at cycle frequencies related to both the symbol rate and the chip rate. Moreover, it is pointed out that the discrete-time signal obtained by uniformly sampling a continuous-time long-code DS-SS signal exhibits cyclostationarity, provided that at least two samples per chip are taken. Finally, it is shown how such a cyclostationarity can be suitably exploited for blind signal-parameter estimation