CFO robust blind receivers for MIMO-OFDM systems based on PARALIND factorizations

Abstract

Carrier frequency offsets (CFO) is a well known impairment that destroys the orthogonality amongst subcarriers in multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, and the resulting inter-carrier interference significantly degrades the performance of such systems. This paper proposes the CFO robust blind receivers for MIMO-OFDM systems based on parallel profiles with linear dependencies (PARALIND) factorizations. First, we model MIMO-OFDM signal in the presence of CFO to satisfy the PARALIND model, where the symbols, the CFO, and the MIMO channel matrices can be viewed as three independent factor matrices. Such a hybrid tensorial modeling enables a blind and joint estimation of symbols and CFO. Then, in order to improve the fitting precision of the PARALIND model, we introduce two algorithms for fitting the PARALIND model. The first one, called delta alternating least squares (DALS) algorithm, where we predict coarsely by exploiting the increment values between two iterations of the factor matrices, refine these predictions by using the enhanced line search and use these refined values to initialize factor matrices, this procedure helps us avoid the random initialization found in the traditional ALS algorithm. The second one, called orthogonal DALS (ODALS) algorithm that uses the solution of orthogonal constraint for the DALS algorithm to provide the initialization for one more factor matrix. The performance of proposed receivers is illustrated by means of simulation results, and a comparison is made with other approaches that allow to estimate symbols and CFO in two separated steps. Beside a robust to CFO characteristics, our approach gives a better BER performance than other compared blind approaches.