A Simple ML Detection for Coded Generalized Frequency Division Multiplexing in MIMO Channels

Generalized frequency division multiplexing (GFDM) is a promising multicarrier scheme, which has shown to be a good candidate to meet the rising demands of 5G networks. The inherent self-interference of GFDM prohibits the direct utilization of maximum likelihood (ML) detection of space-time coding (STC) in multi-input multi-output (MIMO) channels. Recently, a modified version of GFDM, called coded GFDM (CGFDM), has been proposed, which solves the problem of interference mitigation. In this paper, a simple near-optimal ML detection of Alamouti STC is proposed for MIMO CGFDM. Simulation results show that without sacrificing bandwidth efficiency, the proposed scheme outperforms the current MINIO GFDM detection techniques in terms of BER and computational complexity.