摘要
In downlink multi-user multi-input multi-output （MU-MIMO） system, not every user （user equipment （UE）） can calculate accurately signal to interference and noise ratio （SINR） without prior knowledge of the other users＇ precoding vector. To solve this problem, this article proposes a channel inversion precoding scheme by using the lower bound of S1NR and zero-forcing （ZF） algorithm. However, the SINR mismatch between lower bound SINR and actual SINR causes the inaccurateness of adaptive modulation and coding （AMC）. As a result, it causes degradation in performance. Simulation results show that channel inversion precoding provides lower throughput than that of single user multi-input multi-output （SU-MIMO） at high signal-to-noise ratio （SNR） （〉14 dB）, due to the SINR mismatch, although the sum-rate of channel inversion precoding is higher than that of SU-MIMO at full SNR regime.
In downlink multi-user multi-input multi-output （MU-MIMO） system, not every user （user equipment （UE）） can calculate accurately signal to interference and noise ratio （SINR） without prior knowledge of the other users＇ precoding vector. To solve this problem, this article proposes a channel inversion precoding scheme by using the lower bound of S1NR and zero-forcing （ZF） algorithm. However, the SINR mismatch between lower bound SINR and actual SINR causes the inaccurateness of adaptive modulation and coding （AMC）. As a result, it causes degradation in performance. Simulation results show that channel inversion precoding provides lower throughput than that of single user multi-input multi-output （SU-MIMO） at high signal-to-noise ratio （SNR） （〉14 dB）, due to the SINR mismatch, although the sum-rate of channel inversion precoding is higher than that of SU-MIMO at full SNR regime.
基金
supported by the National Natural Science Foundation of China (60602058)
the Hi-Tech Research and Development Program of China (2006AA01Z257)
