Research On Detection Methods For Massive MIMO BDMA Downlink

With the rapid development of mobile communication technology, massive multi-input multi-output (MIMO) has raised more and more research interest. The massive MIMO Beam Division Multiple Access (BDMA) transmission has been proposed as a practical scheme for massive MIMO transmission in the fifth-generation (5G) mobile communication systems. By using the beam domain channel characteristics of mas-sive MIMO, it decomposes the MU-MIMO channels into multiple equivalent single-user MIMO channels, which results in significant decrease of the transceiver processing complexity. This thesis is mainly focused on the detection methods for massive MIMO BDMA downlink.Firstly, we investigate the sorted QR detection algorithms for massive MIMO BDMA downlink to mit-igate the interuser interference and reduce the receiver complexity. According to the system model, we present the formulation of the received signal at the receiver, as well as the linear minimum mean square error (MMSE) detection algorithm and zero forcing (ZF) sorted QR decomposition (SQRD) soft interference cancellation (SIC) detection algorithm. Based on these two algorithms, we further give the MMSE SQRD SIC and modified MMSE SQRD SIC detection algorithms using extended matrix. Considering the poor bit error ratr (BER) performance of the ZF SQRD SIC detection algorithm and the high complexity of MMSE detection algorithms, we propose a MMSE SQRD based on regularization SIC detection algorithm by intro-ducing a regularization parameter in extended matrix. Simulation results show that the proposed algorithm has a good detection performance as well as a low complexity.Secondly, we investigate the interpolation-based SQRD detection algorithms for wideband massive MI-MO BDMA downlink to reduce the receiver complexity. We first describe the relation between the MIMO transfer function and Laurent polynomial matrix. Then, three interpolation methods are presented for Laurent polynomial matrix. Furthermore, the interpolation-based QR decomposition and parallel SQRD detection method are introduced. We combine these two methods with the sorted QR detection algorithms to derive the interpolation-based SQRD detection algorithms for massive MIMO BDMA downlink. Then, we evaluate the complexity of the interpolation-based ZF parallel SQRD SIC and interpolation-and-regularization-based MMSE parallel SQRD SIC detection algorithms. Simulation results indicate that interpolation-based SQRD detection algorithms for massive MIMO BDMA downlink can significantly reduce the complexity while keeping a good BER performance.Finally, we investigate the iterative interference cancellation detection algorithms for massive MIMO BDMA downlink. Based on the model of iterative receiver, we describe the iterative processing of interact-ing soft information between the soft-input soft-output (SISO) MIMO detector and the SISO Turbo decoder, which shows the principle of the iterative receiver. For the case with strong interference signal, we give a sin-gle user MMSE iterative detection algorithm for massive MIMO BDMA downlink. Based on this algorithm, we further propose an interference-cancellation-based MMSE iterative detection algorithm. Simulation result-s show that the interference-cancellation-based MMSE iterative detection algorithm obtains a significant BER performance gain over the single user MMSE iterative detection algorithm but at the cost of some implemen-tation complexity. The simulation results also show that the advantage of the interference-cancellation-based MMSE iterative detection algorithm with more channel information is reduced and the BER performance of these two MMSE iterative detection algorithms tends to be the same when the modulation order and code rate increase.