Low complexity detection algorithm for under-determined MIMO systems

A low complexity detection algorithm based on list sphere decoding (LSD) is proposed for under-determined multiple-input multiple-output (UD-MIMO) systems with N transmit antennas and M <; N receive antennas. The proposed algorithm utilizes the unique structure of UD-MIMO systems by dividing the N detection layers into two groups. Group 1 contains layers 1 to M that have similar structures as a symmetric MIMO system; while Group 2 contains layers M + 1 to N that contribute to the rank deficiency of the channel Gram matrix. Tree search algorithms are used for both groups, but with different search radii. A new method is proposed to adaptively adjust the tree search radius of Group 2 based on the statistical properties of the received signals. The employment of the adaptive tree search can significantly reduce the computational complexity. Simulation results show that the proposed algorithm can reduce the complexity by one orders of magnitude with less than 0.01 dB degradation in the Bit-Error-Rate (BER) performance.