Efficient Detectors based on Group Detection for Massive MIMO systems

Abstract

In Multiple Input Multiple Output (MIMO) systems, the complexities of detectors depend on the size of the channel matrix. In Massive MIMO systems, detection complexity becomes remarkably higher because the dimensions of the channel matrix get much larger. In order to recover the signals in the up-link of a Massive MIMO system at reduced complexities, we first divide the system into two sub-systems. After that, we apply the Minimum Mean Square Error (MMSE) and Bell Laboratory Layer Space Time (BLAST) detectors to each subsystem, resulting in the so-called MMSE-GD and BLAST-GD detectors, respectively. To further enhance the BER performance of Massive MIMO systems under the high-load conditions, we propose two additional detectors, called MMSE-IGD and BLAST-IGD by respectively applying the conventional MMSE and BLAST on the sub-systems in an iterative manner. It is shown via computer simulation and analytical results that the proposed detectors enable the system to achieve not only higher BER performance but also low detection complexities as compared to the conventional linear detectors. Moreover, the MMSE-IGD and BLAST-IGD can significantly improve BER performance of Massive MIMO systems.