• DocumentCode
    272014
  • Title

    Low-complexity linear precoding for multi-cell massive MIMO systems

  • Author

    Kammoun, Abla ; Muller, A. ; Bjornson, Emil ; Debbah, Mérouane

  • Author_Institution
    King Abdullah Univ. of Sci. & Technol., Thuwal, Saudi Arabia
  • fYear
    2014
  • fDate
    1-5 Sept. 2014
  • Firstpage
    2150
  • Lastpage
    2154
  • Abstract
    Massive MIMO (multiple-input multiple-output) has been recognized as an efficient solution to improve the spectral efficiency of future communication systems. However, increasing the number of antennas and users goes hand-in-hand with increasing computational complexity. In particular, the precoding design becomes involved since near-optimal precoding, such as regularized-zero forcing (RZF), requires the inversion of a large matrix. In our previous work [1] we proposed to solve this issue in the single-cell case by approximating the matrix inverse by a truncated polynomial expansion (TPE), where the polynomial coefficients are selected for optimal system performance. In this paper, we generalize this technique to multi-cell scenarios. While the optimization of the RZF precoding has, thus far, not been feasible in multi-cell systems, we show that the proposed TPE precoding can be optimized to maximize the weighted max-min fairness. Using simulations, we compare the proposed TPE precoding with RZF and show that our scheme can achieve higher throughput using a TPE order of only 3.
  • Keywords
    MIMO communication; computational complexity; linear codes; matrix inversion; minimax techniques; precoding; RZF; TPE order; communication systems; computational complexity; low-complexity linear precoding; matrix inversion; multicell massive MIMO systems; multiple-input multiple-output systems; near-optimal precoding; optimal system performance; regularized-zero forcing; single-cell case; spectral efficiency improvement; truncated polynomial expansion; weighted max-min fairness; Antennas; Covariance matrices; Interference; MIMO; Optimization; Polynomials; Signal to noise ratio; Massive MIMO; linear precoding; low complexity; multi-cell systems; random matrix theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
  • Conference_Location
    Lisbon
  • Type

    conf

  • Filename
    6952770