Index modulation (IM) is a novel digital modulation technique, which inactivates some subcarriers in orthogonal frequency division multiplexing (OFDM) to exploit the indices of the subcarriers to transmit bits implicitly, and has potential to further improve the energy efficiency and error performance. For the multiple-input multiple-output- (MIMO-) aided IoT devices, a highly efficient and low-complexity IM-aided scheme is needed to reduce the computational complexity at the receiver sides. In this paper, we propose a novel highly efficient MIMO-OFDM with IM scheme by performing IM on each transmit antenna subgroup, which contains two transmit antennas, to achieve two transmit diversity order and significant reduction in computational complexity at the cost of a minor spectral efficiency. To reduce the demodulation complexity, a low-complexity sequential Monte Carlo (SMC) theory-based detector is proposed, which exploits the null space submatrix of the preprocessed channel response matrix by using QR decomposition, to calculate the most likely transmitted IM patterns before the detection of the modulated symbols. Computer simulation results and complexity analysis show that the proposed IM-aided scheme achieves better error performance with extremely low computational complexity under the same constellation and the proposed SMC detector has potential to achieve near optimal bit error rate performance with considerably low demodulation complexity.