This letter deals with joint carrier frequency offset (CFO) and direction of arrival (DOA) estimation based on the minimum variance distortionless response (MVDR) criterion for interleaved orthogonal frequency division multiple access (OFDMA)/space division multiple access (SDMA) uplink systems. In order to reduce the computational load of two-dimensional searching based methods, the proposed method includes only once polynomial CFO rooting and does not require DOA paring, hence it raises the searching efficiency. Several simulation results are provided to illustrate the effectiveness of the proposed method.

In this letter, standard particle swarm optimization (PSO) with the center-symmetric trimmed correlation matrix and the orthogonal projection technique is firstly presented for blind carrier frequency offset estimation under interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. It doesn't require eigenvalue decomposition and only needs a single OFDMA data block. Second, this letter also presents adaptive multiple inertia weights with Newton method to speed up the convergence of standard PSO iteration process. Meanwhile, the advantage of inherent interleaved OFDMA signal structure also is exploited to conquer the problems of local optimization and the effect of ambiguous peaks for the proposed approaches. Finally, several simulation results are provided for illustration and comparison.

This letter deals with the carrier frequency offsets (CFO) estimation problem for orthogonal frequency division multiple access (OFDMA) uplink systems. Combined with centro-symmetric (CS) trimmed autocorrelation matrix and weighting subspace projection, the proposed estimator has better estimate performance than MVDR, MUSIC, CS-MUSIC, and ESPRIT estimators, especially in relatively less of OFDMA blocks and low SNR situations. Simulation results are presented to verify the efficiency of the proposed estimator.

In this letter, an iterative carrier frequency offset (CFO) estimation approach is presented which finds a new CFO vector based on first order Taylor series expansion of the one initially given for interleaved orthogonal frequency division multiple access uplink systems. The problem of finding the new CFO vector is formulated as the closed form of a generalized eigenvalue problem, which allows one to readily solve it. The proposed estimator combined center-symmetric trimmed correlation matrix and orthogonal projection technique, which doesn't require eigenvalue decomposition and it only needs single data block.

This paper deals with carrier frequency offset (CFO) estimation based on the minimum variance distortionless response (MVDR) criterion without using specific training sequences for interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. In the presence of large CFOs, the estimator is proposed to find a new CFO vector based on the first-order Taylor series expansion of the one initially given. The problem of finding the new CFO vector is formulated as the closed form of a generalized eigenvalue problem, which allows one to readily solve it. Since raising the accuracy of residual CFO estimation can provide more accurate residual CFO compensation, this paper also present a decision-directed MVDR approach to improve the CFO estimation performance. However, the proposed estimator can estimate CFOs with less computation load. Several computer simulation results are provided for illustrating the effectiveness of the proposed blind estimate approach.

This letter deals with blind carrier frequency offset estimation by exploiting the minimum variance distortionless response (MVDR) criterion for interleaved uplink orthogonal frequency division multiple access (OFDMA). It has been shown that the complexity and estimation accuracy of MVDR strictly depend on the grid size used during the search. For the purpose of efficient estimation, we present an improved polynomial rooting estimator that is robust in low signal-to-noise ratio scenario. Simulation results are provided for illustrating the effectiveness of the proposed estimator.