Low-complexity iterative channel estimation with lattice reduction-based detection for multiple-input multiple-output systems

Iterative channel estimation and detection (ICED) can provide a better performance as the channel estimation can be improved through iterations. For a multiple-input multiple-output channel, owing to a large size of the signal alphabet, ICED becomes less practical unless a low-complexity detector such as a lattice reduction-based detector is employed. However, since the lattice basis reduction has to be carried out for each iteration, the resulting complexity can be still high. In this study, a computationally efficient technique was proposed to perform the lattice basis reduction within ICED over both static and slowly time-varying block-fading channels, where orthogonal defect of basis, as well as error probability are considered to decide whether or not basis reduction is needed for each iteration.