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In massive multiple-input multiple-output (MIMO) systems when the number of base station antennas is much higher than the number of users, linear detectors, such as zero forcing (ZF) and minimum mean-square error (MMSE), are able to achieve the near-optimal performance due to the favorable massive MIMO channel propagation. But, these detectors employ, in general, exact matrix inversion which is computationally...
Minimum mean square error (MMSE) linear detector has been considered as one of the potential detection algorithm for uplink multi-user massive MIMO systems, because it can achieve the near-optimal bit error rate (BER) performance. However, it involves matrix inversion with high complexity. Thus, the conventional Gauss-Seidel (GS) method has been applied for obtain a low-complexity MMSE detector without...
In massive multiple-input multiple-output (MIMO) systems, with the increase of the number of received antennas at base station (BS), the linear detectors, as minimum mean-square error (MMSE), are able to achieve the near-optimal performance. However, these detectors involve matrix inversion with high complexity. Thus, in order to reduce the complexity, Neumann Series (NS) expansion has been proposed...
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