In this paper, we propose a low complexity multipleinputmultiple-output (MIMO) detection algorithm with adaptiveinterference mitigation in downlink multiuser MIMO (DL MUMIMO)systems with quantization error of the channel state information(CSI) feedback. In DL MU-MIMO systems using theimperfect precoding matrix caused by quantization error of theCSI feedback, the station receives the desired signal as well as theresidual interference signal. Therefore, a complexMIMO detectionalgorithm with interference mitigation is required for mitigatingthe residual interference. To reduce the computational complexity,we propose a MIMO detection algorithm with adaptive interferencemitigation. The proposed algorithm adaptively mitigates theresidual interference by using the maximum likelihood detection(MLD) error criterion (MEC). We derive a theoretical MEC byusing the MLD error condition and a practical MEC by approximatingthe theoretical MEC. In conclusion, the proposed algorithmadaptively performs interference mitigation when satisfyingthe practical MEC. Simulation results show that the proposed algorithmreduces the computational complexity and has the sameperformance, compared to the generalized sphere decoder, whichalways performs interference mitigation.

In this paper, we propose a low complexity multiple-input multiple-output (MIMO) detection algorithm with adaptive interference mitigation in downlink multiuser MIMO (DL MU-MIMO) systems with quantization error of the channel state information (CSI) feedback. In DL MU-MIMO systems using the imperfect precoding matrix caused by quantization error of the CSI feedback, the station receives the desired signal as well as the residual interference signal. Therefore, a complex MIMO detection algorithm with interference mitigation is required for mitigating the residual interference. To reduce the computational complexity, we propose a MIMO detection algorithm with adaptive interference mitigation. The proposed algorithm adaptively mitigates the residual interference by using the maximum likelihood detection (MLD) error criterion (MEC). We derive a theoretical MEC by using the MLD error condition and a practical MEC by approximating the theoretical MEC. In conclusion, the proposed algorithm adaptively performs interference mitigation when satisfying the practical MEC. Simulation results show that the proposed algorithm reduces the computational complexity and has the same performance, compared to the generalized sphere decoder, which always performs interference mitigation.