Efficient Initialization of Iterative Linear Massive MIMO Uplink Detectors by Binary Jacobi Synthesis

In this paper, we propose a decentralized feedforward initialization approach for iterative equalization methods, that decomposes a massive MIMO system into multiple smaller subsystems, where successively combining pairs of these systems and their solutions using the Jacobi method results in a high quality initial estimate for a following iterative detection method. In contrast to existing methods, this approach allows a computation of an initial estimate while the Gram matrix and matched filter output vector is not fully available. The BER performances show the effectiveness of this initialization method compared to approaches like maximum-ratio combining at high basestationto- client antenna ratios.