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 precoding schemes can achieve near-optimal performance in massive MIMO systems. However, classical linear precoding 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- complexity precoding 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-based precoding can reduce the complexity of ZF precoding by about one order of magnitude. Simulation results verify that the proposed LSQR-based precoding can provide a better tradeoff between complexity and performance than the recently proposed Neumann-based precoding.


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    Title :

    Low-Complexity LSQR-Based Linear Precoding for Massive MIMO Systems


    Contributors:
    Xie, Tian (author) / Lu, Zhaohua (author) / Han, Qian (author) / Quan, Jinguo (author) / Wang, Bichai (author)


    Publication date :

    2015-09-01


    Size :

    139704 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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