Multiuser MIMO system using block space–time spreading and tensor modeling

In this paper, we consider a point-to-multipoint downlink multiuser wireless communication system, where a multiple-antenna base station simultaneously transmits data to several users equipped with multiple receive antennas. The transmit antenna array is partitioned into transmission blocks, each one being associated with a given user. Space–time spreading is performed within each block using a transmit antenna subset. We formulate block space–time spreading using a tensor modeling. We show that the tensor-based block space–time spreading model has the distinguishing feature of modeling a multiuser space–time transmission with different spatial spreading factors (diversity gains) as well as different multiplexing factors (code rates) for the users. The space–time spreading structure is chosen to allow a deterministic multiuser interference (MUI) elimination by each user. A block-constrained tensor model is then presented for the received signal, which is characterized by fixed constraint matrices that reveal the overall space–time spreading pattern. At each receiver, blind joint channel and symbol recovery is performed using an alternating least squares algorithm. Simulation results illustrate the performance of the proposed transceiver model in terms of bit-error-rate, channel/symbol estimation accuracy and link-level throughput.