A low-complexity blind timing algorithm is proposed to estimate timing offset in OFDM systems when multiple symbols are received (the timing offset estimation is independent of the frequency offset one). Though the maximum-likelihood estimation (MLE) using two or three symbols is good in offset estimation, its performance can be significantly improved by including more symbols in our previous work. However, timing offset estimation requires exhaustive search and a priori knowledge of the probability distribution of the received data. The method we propose utilizes the second-order statistics embedded in a cyclic prefix. An information vector (IVR) with the same length as the cyclic prefix is formed based on an autocorrelation matrix (AM). T...
In this paper, we present a data-based method for simultaneous Maximum Likelihood (ML) symbol timing...
Abstract – We present a method for the joint estimation of timing and carrier-frequency offset in Or...
This paper proposes a novel non-data-aided maximum likelihood (ML) approach for the estimation of th...
In this correspondence, we consider the problem of blind symbol timing (ST) estimation for pulse-sha...
In this paper, an estimated weighting factor and two symbol timing estimators are proposed for timin...
Abstract—An efficient synchronization scheme based on a repetitive preamble structure for orthogonal...
In this paper, we present a novel data-based method for simultaneous Maximum Likelihood (ML) symbol ...
We present two new blind symbol time and carrier frequency offset estimators for OFDM systems, in a ...
We present a blind coarse timing offset estimation technique for CP-OFDM and ZP-OFDM transmission ov...
In this paper, we present a novel data-based method for simultaneous Maximum Likelihood (ML) symbol ...
A new algorithm for the timing offset estimation for Orthogonal Frequency Division Multiplexing (OFD...
The paper deals with the problem of blind synchronization for OFDM/OQAM systems. Specifically, by ex...
In this paper, a blind symbol synchronization algorithm is presented for orthogonal frequency-divisi...
This paper presents a symbol time offset estimator for coherent orthogonal frequency division multip...
We present a novel approach for carrier frequency offset estimation in OFDM systems. Before they ent...
In this paper, we present a data-based method for simultaneous Maximum Likelihood (ML) symbol timing...
Abstract – We present a method for the joint estimation of timing and carrier-frequency offset in Or...
This paper proposes a novel non-data-aided maximum likelihood (ML) approach for the estimation of th...
In this correspondence, we consider the problem of blind symbol timing (ST) estimation for pulse-sha...
In this paper, an estimated weighting factor and two symbol timing estimators are proposed for timin...
Abstract—An efficient synchronization scheme based on a repetitive preamble structure for orthogonal...
In this paper, we present a novel data-based method for simultaneous Maximum Likelihood (ML) symbol ...
We present two new blind symbol time and carrier frequency offset estimators for OFDM systems, in a ...
We present a blind coarse timing offset estimation technique for CP-OFDM and ZP-OFDM transmission ov...
In this paper, we present a novel data-based method for simultaneous Maximum Likelihood (ML) symbol ...
A new algorithm for the timing offset estimation for Orthogonal Frequency Division Multiplexing (OFD...
The paper deals with the problem of blind synchronization for OFDM/OQAM systems. Specifically, by ex...
In this paper, a blind symbol synchronization algorithm is presented for orthogonal frequency-divisi...
This paper presents a symbol time offset estimator for coherent orthogonal frequency division multip...
We present a novel approach for carrier frequency offset estimation in OFDM systems. Before they ent...
In this paper, we present a data-based method for simultaneous Maximum Likelihood (ML) symbol timing...
Abstract – We present a method for the joint estimation of timing and carrier-frequency offset in Or...
This paper proposes a novel non-data-aided maximum likelihood (ML) approach for the estimation of th...