Reduced-rank widely linear precoding in Massive MIMO systems with I/Q imbalance

We present reduced-rank widely linear precoding algorithms for Massive MIMO systems with I/Q imbalance (IQI). With a large number of transmit antennas, the imperfection I/Q branches at the transmitter has a significant impact on the downlink performance. We develop linear precoding techniques using an equivalent real-valued model to mitigate IQI and multiuser interference. In order to reduce the computational complexity required by the matrix inverse, a widely linear reduced-rank precoding strategy based on the Krylov subspace (KS) is devised. Simulation results show that the proposed methods work well under IQI, and the KS precoding algorithm performs almost as well as the full-rank precoder while requiring much lower complexity.