Feedback Interference Cancellation Detection for quantized Massive MIMO Systems

In this paper, a Bussgang-based feedback interference cancellation (BFIC) algorithm is proposed for low-resolution quantized massive multiple-input multiple-output (MIMO) systems. Different from the traditional zero-forcing-based (ZF-based) Bussgang successive interference cancellation (BSIC) that only takes the detected symbols into account to remove the inter-symbol interference, the proposed BFIC algorithm adopts the optimized low-complexity Bussgang minimum mean squared error (BMMSE) filter and handles the interference from the undetected symbols via an iterative feedback filtering, leading to the remarkable performance gain. By reformulating the iterative operations as an incremental form, we show that the iteration update can be further optimized. Moreover, an update ordering criterion regarding to the proposed BFIC algorithm is given for reducing the possible error propagation with low complexity. Finally, simulation results are presented to illustrate the performance gains of the proposed BFIC algorithm.