Error propagation can seriously affect the performance of an adaptive decision feedback equaliser (DFE), especially when operated in time-varying channel environments. Error propagation not only affects DFE decisions, but also disturbs the DFE adaptation. The paper focuses on improving the robustness against error propagation for the least-mean-square (LMS) based minimum mean-squared-error DFE (MMSE-DFE). A specifically designed channel estimator is introduced to help the DFE adaptation in the decision-directed (DD) mode. Unlike the conventional DFE, the proposed adaptive channel-aided DFE (ACA-DFE) only adapts the feedforward filter with the LMS algorithm. The feedback filter, however, is obtained from the postcursors of the estimated channel convolved with the feedforward filter. As a result, the proposed ACA-DFE can reduce the error propagation effect and perform better than the conventional adaptive DFE. We also demonstrate that the ACA-DFE can be extended to multiple-input multiple-out (MIMO) systems improving the performance of the conventional MIMO DFE.