Search

In this letter, an efficient detection scheme is proposed to mitigate the effect of the carrier frequency offset (CFO) in spatial modulation orthogonal frequency division multiplexing (SM-OFDM) systems. Specifically, the proposed scheme employs a novel symbol-by-symbol-aided iterative detector to the SM-OFDM systems with multiple CFOs, where the zero symbols are considered as constellation points. Simulation results demonstrate that the proposed scheme is capable of effectively mitigating the effect of multiple CFOs and of providing about considerable system performance improvement compared with the conventional parallel interference cancellation-aided maximum likelihood detector at a moderate complexity cost.

In this letter, a novel low-complexity detector based on the concept of compressive sensing (CS) is proposed for a novel multiple-input multiple-output system, namely, quadrature spatial modulation (QSM). In particular, the CS algorithm is performed in the real-valued system model, and the activated antenna indices, which are used to transmit the real and imaginary parts of QSM symbols, can be estimated separately. In order to further improve the performance of QSM, a novel search strategy is proposed. Simulation results show that the proposed detector is capable of achieving a considerable reduction in complexity compared with the maximum likelihood counterpart with negligible performance loss.

Differential spatial modulation (DSM), which does not require the channel state information at the receiver, is an attractive alternative to its coherent counterpart. The optimal maximum-likelihood (ML) detector of the DSM system employs the classic block-by-block method for jointly detecting the activated antenna matrix (AM) and the modulation symbols, resulting in high computational complexity. In this letter, a low-complexity near-ML detector, which operates on a symbol-by-symbol basis, is proposed for the DSM scheme. Specifically, in each block, the index of the activated transmit antenna and modulation symbol in each time slot are first obtained, and then, these antenna indices are utilized to simply determine the index of the activated AM. Simulation results show that the proposed algorithm is capable of offering almost the same performance as that of the ML detector with more than 90% reduction in complexity.