Iterative Sparse Interference Cancelation Algorithm for Massive MIMO Uplink System

ABSTRACT We investigate an iterative sparse interference cancelation (ISIC) algorithm in massive multiple input multiple output (MIMO) uplink systems, which includes a multilayer implementation consisting of a channel sparse estimation layer using an improved Sparsity Adaptive Matching Pursuit (SAMP) algorithm, sorting layer and filtering layer with noise power threshold. The theoretical bound for noise power threshold is also addressed. To optimize sparse interference cancelation, we analyze its feasibility and robustness with an iterative scheme detecting the symbols sequentially and eliminating interference from all other users at different multiuser access conditions. Additionally, we provide theoretical proof for iteration termination condition. Analysis and simulation also demonstrate the performance of our proposed sparse interference cancelation approach ideal maximum likelihood (ML) detection under different multiuser access conditions.