An overloaded MIMO signal detection scheme with slab decoding and lattice reduction

This paper proposes a reduced complexity signal detection scheme for overloaded MIMO (Multiple-Input Multiple-Output) systems. The proposed scheme firstly divides the transmitted signals into two parts, the post-voting vector containing the same number of signal elements as of receive antennas, and the pre-voting vector containing the remaining elements. Secondly, it uses slab decoding to reduce the solution candidates of the pre-voting vector and determines the post-voting vectors for each pre-voting vector candidate by lattice reduction aided MMSE (Minimum Mean Square Error)-SIC (Successive Interference Cancellation) detection. Simulation results show that the proposed scheme can achieve almost the same performance as the optimal ML (Maximum Likelihood) detection while drastically reducing the required computational complexity.