Low Complexity Iterative MMSE-PIC Detection for Medium-Size Massive MIMO

Abstract

In medium-size massive MIMO systems, the minimum mean-square-error parallel interference cancellation (MMSE-PIC)-based soft-input soft-output (SISO) detector is often used due to its relatively low complexity and good bit error rate (BER) performance. The computational complexity of MMSE-PIC for detecting a block of data is dominated by the computation of a Gram matrix and a matrix inversion. They have computational complexity of $\mathcal{O}(K^2M)$ and $\mathcal{O}(K^3)$ , respectively, where $K$ is the number of uplink users with one transmit antenna each and $M$ is the number of receive antennas at the base station. In this letter, by using an $L$ (typically $L \leq 3$ ) terms of Neumann series expansion to approximate the matrix inversion, we reduce the total computational complexity to $\mathcal{O}(LKM)$ . Compared with alternative algorithms, which focus on reducing the complexity of the matrix inversion only, the proposed method can also avoid calculating the Gram matrix explicitly and thus significantly reducing the total complexity.