Iterative detection and decoding in 3GPP LTE-based massive MIMO systems

Massive multiple-input multiple-output (MIMO) is expected to be a key technology in next-generation multi-user cellular systems for achieving higher throughput and better link reliability than existing (small-scale) MIMO systems. In this work, we develop a novel, low-complexity iterative detection and decoding algorithm for single carrier frequency division multiple access (SC-FDMA)-based massive MIMO systems, such as future 3GPP LTE-based systems. The proposed algorithm combines a novel frequency-domain minimum mean-square error (FD-MMSE) equalization method with parallel interference cancellation (PIC), requires low computational complexity, and achieves near-optimal error-rate performance in 3GPP-LTE-based massive MIMO systems having only 2× more base-station antennas than users.