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Low-complexity and Statistically Robust Beamformer Design for Massive MIMO Systems. (arXiv:1711.11405v1 [cs.IT])
来源于:arXiv
Massive MIMO is a variant of multiuser MIMO in which the number of antennas
at the base station (BS) $M$ is very large and typically much larger than the
number of served users (data streams) $K$. Recent research has illustrated the
system-level advantages of such a system and in particular the beneficial
effect of increasing the number of antennas $M$. These benefits, however, come
at the cost of dramatic increase in hardware and computational complexity. This
is partly due to the fact that the BS needs to compute suitable beamforming
vectors in order to coherently transmit/receive data to/from each user, where
the resulting complexity grows proportionally to the number of antennas $M$ and
the number of served users $K$. Recently, different algorithms based on tools
from random matrix theory in the asymptotic regime of $M,K \to \infty$ with
$\frac{K}{M} \to \rho \in (0,1)$ have been proposed to reduce the complexity.
The underlying assumption in all these techniques, however, is that 查看全文>>