Abstract
Signal detection algorithm based on the linear minimum mean square error (LMMSE) criteria can achieve quasi-optimal performance in uplink of massive MIMO systems where the base stations are equipped with hundreds of antennas. However, it introduces complicated matrix inversion operations, thus making it prohibitively difficult to implement rapidly and effectively. In this paper, we first propose a low complexity signal detection approach by exploiting the weighting symmetric successive over-relaxation (WSSOR) iterative method to circumvent the computations in the matrix inversion. We then present a proper initial solution, relaxation parameter, and scope of the weighting factor to accelerate the convergence speed. Simulation results prove that the proposed simplified method can reach its performance quite close to that of the LMMSE algorithm with no more than three iterations.
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Acknowlegement
This work was supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China (Grant No. 2015ZX03001033-002).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Quan, H., Ciocan, S., Qian, W., Bin, S. (2018). Low-Complexity MMSE Signal Detection Based on WSSOR Method for Massive MIMO Systems. In: Chen, Q., Meng, W., Zhao, L. (eds) Communications and Networking. ChinaCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 210. Springer, Cham. https://doi.org/10.1007/978-3-319-66628-0_19
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DOI: https://doi.org/10.1007/978-3-319-66628-0_19
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