Massive multiple-input multiple-output (MIMO) using a large number of antennas at the base station (BS) is a promising technique for the next-generation 5G wireless communications. It has been shown that linear precod...
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ISBN:
(纸本)9781479980925
Massive multiple-input multiple-output (MIMO) using a large number of antennas at the base station (BS) is a promising technique for the next-generation 5G wireless communications. It has been shown that linearprecoding schemes can achieve near-optimal performance in massive MIMO systems. However, classical linearprecoding schemes such as zero-forcing (ZF) precoding suffer from high complexity due to the fact they require the matrix inversion of a large size. In this paper, we propose a low-complexityprecoding scheme based on the least square QR (lsqr) method to realize the near-optimal performance of ZF precoding without matrix inversion. We show that the proposed lsqr-basedprecoding can reduce the complexity of ZF precoding by about one order of magnitude. Simulation results verify that the proposed lsqr-basedprecoding can provide a better tradeoff between complexity and performance than the recently proposed Neumann-basedprecoding.
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