As a hybrid MIMO architecture, beamspace multiple input multiple output (MIMO) can significantly reduce the number of required radio frequency (RF) chains in millimeter wave (mmWave) massive MIMO systems without obvious performance loss, in which, however, the number of users supported cannot be larger than that of RF chains. To break this fundamental limit, we introduce the concept of code-domain non-orthogonal multiple access (NOMA) into beamspace MIMO. A beam selection scheme is proposed first to maximize the sum-rate by utilizing the quasi-orthogonality of the beamspace channel. Furthermore, a low-complexity detection algorithm is developed to realize the transceiver design in mmWave communications using lens antennas. Finally, numerical results of the decoding complexity at receiver side are analyzed. Simulation results show that the proposed beamspace MIMO-NOMA in code domain can achieve higher spectrum and energy efficiency compared with the existing beamspace MIMO.

The newly proposed sparse-code multiple-access (SCMA) has been shown to approach the single-user performance even the overload reaches 150% when message passing algorithm (MPA) detection is applied. Obviously, combined with multiple-input multiple-output (MIMO) techniques, the spectrum efficiency of SCMA system can be further improved. While maximum likelihood (ML) detection is optimal for MIMO-SCMA, the detection complexity would grow exponentially when the number of both the antennas and users increase. In this paper, we propose a novel low complexity joint MPA detection scheme for downlink MIMO-SCMA to utilize the sparsity of the channel and codeword. The analysis and simulation results show that compared with ML detection, the proposed joint MPA can decrease the complexity significantly while keep the BER performance unchanged.

In this paper, a general framework of the multiple- input multiple-output (MIMO) transceiver design for 5G multiple access (5GMA), including both non- orthogonal multiple access (NOMA) and sparsity code multiple access (SCMA), is developed to enhance the system throughput of next generation of communication systems. By applying generalized singular value decomposition (GSVD), MIMO channels can be decomposed into multiple single-input single- output (SISO) channels, to which the concept of NOMA and SCMA can ideally be applied. GSVD based precoding is proposed to both uplink and downlink 5GMA transmissions, and simulation results are provided to demonstrate the performance of the proposed schemes.