Iterative Sparse Interference Cancellation Algorithm for Non-Stationary Massive MIMO Uplink System Based on ZF Filter

In this paper, we introduce the sparse interference cancellation scheme in non-stationary massive MIMO uplink systems. Due to the sparsity for non-stationary massive MIMO, we propose the multi-layer implementation method for constructing sparse interference cancellation algorithm, which consist of multiple layers including channel sparse estimation layer using an improved SAMP, sorting layer and filtering layer through comparing with noise power threshold. The theoretical proof of noise power threshold power is proved. By constructing sparse ZF filter, we also analyze its feasibility and robustness under different multi-user access conditions through simulation. Then, we proposed the iterative methods based on sparse ZF scheme to reduce the complexity. Symbols would be sequentially detected and eliminated interference from all other users at every iteration. We also provide an iteration termination condition based on the IC algorithm and provide the theoretical proof. Furthermore, we proposed preprocessing method based on channel power reordering. Analysis and simulation results show that under different milt-user access, the performance of our proposed sparse interference cancellation approach ideal MAP detection.