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A projected fast ISTA algorithm for joint beam forming and antenna selection in massive MIMO

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Abstract

The joint beam-forming and antenna selection problem encountered in modern multi-user massive multiple input multiple output (MIMO) communication systems is solved using the projected fast iterative shrinkage–thresholding algorithm (ISTA). The algorithm aim is to find the suboptimal set of transmitting antennas and to calculate the suboptimal beamforming weights which maximize the users’ achievable data rates. These requirements should be achieved quickly to maintain the system quality and reliability. The numerical analysis shows that the same rates are achieved using projected ISTA and projected fast ISTA. It also shows that the convergence rates for projected fast ISTA are much better than that of projected ISTA, and these rates are independent of the problem size. The paper concluded that the projected fast ISTA is suitable for multiuser massive MIMO systems due to the fast convergence rates and the implementation simplicity even for large system dimensions.

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References

  1. Bliss, D. W., Forsythe, K. W., & Chan, A. M. (2005). MIMO wireless communication. Lincoln Laboratory Journal,15(1), 97–126.

    Google Scholar 

  2. Larsson, E. G., Edfors, O., Tufvesson, F., & Marzetta, T. L. (2014). Massive MIMO for next generation wireless systems. IEEE Communications Magazine,52(2), 186–195.

    Article  Google Scholar 

  3. El-Khamy, S. E., Moussa, K. H., & El-Sherif, A. A. (2015). Performance analysis of massive MIMO multiuser transmit beamforming techniques over generalized spatial channel model. In 32nd national radio science conference (NRSC) (pp. 139–146).

  4. Ng, B. L., et al. (2012). Fulfilling the promise of massive MIMO with 2D active antenna array. In 2012 IEEE globecom workshops, 2012 (pp. 691–696).

  5. Mehmood, Y., Afzal, W., Ahmad, F., Younas, U., Rashid, I., & Mehmood, I. (2013). Large scaled multi-user MIMO system so called massive MIMO systems for future wireless communication networks. In 19th international conference on automation and computing (ICAC), 2013, September (pp. 13–14).

  6. Björnson, E., Matthaiou, M., & Debbah, M. (2014). Circuit-aware design of energy-efficient massive MIMO systems. In 6th international symposium on communications, control and signal processing (ISCCSP) (pp. 101–104).

  7. Bjornson, E., Matthaiou, M., & Debbah, M. (2014). Massive MIMO systems with hardware-constrained base stations. In IEEE international conference on acoustics, speech and signal processing (ICASSP) (pp. 3142–3146).

  8. El-Khamy, S. E., Moussa, K. H., & El-Sherif, A. A. (2016). Performance of enhanced massive multiuser MIMO systems using transmit beamforming and transmit antenna selection techniques. In Wireless personal commununication (pp. 1–14).

  9. Gao, X., Edfors, O., Liu, J., & Tufvesson, F. (2013). Antenna selection in measured massive MIMO channels using convex optimization. In 2013 IEEE globecom workshops (GC Wkshps) (pp. 129–134).

  10. Han, B., Liang, L., & Chen, P. (2017). Joint precoding and scheduling algorithm for massive MIMO in FDD multi-cell network. In Wireless networks (pp. 1–11).

  11. Benmimoune, M., Driouch, E., Ajib, W., & Massicotte, D. (2017). Novel transmit antenna selection strategy for massive MIMO downlink channel. Wireless Networks,23(8), 2473–2484.

    Article  Google Scholar 

  12. Kim, D., Lee, G., & Sung, Y. (2015). Two-stage beamformer design for massive MIMO downlink by trace quotient formulation. IEEE Transactions on Communications,63(6), 2200–2211.

    Article  Google Scholar 

  13. Mehanna, O., Sidiropoulos, N. D., & Giannakis, G. B. (2013). Joint multicast beamforming and antenna selection. IEEE Transactions on Signal Processing,61(10), 2660–2674.

    Article  MathSciNet  Google Scholar 

  14. Zhao, M., Chen, X., Shi, Q., Xu, W., & Member, S. (2018). Joint transmit beamforming and antenna selection in MIMO systems. In IEEE wireless communication letters, Early Access.

  15. Lee, G., Park, J., Sung, Y., & Seo, J. (2012). A new approach to beamformer design for massive MIMO systems based on k-Regularity. In IEEE globecom workshops (GC Wkshps) (pp. 686–690).

  16. Beck, A., & Teboulle, M. (2009). A fast iterative shrinkage–thresholding algorithm. Society for Industrial Applied Mathematics Journal of Imaging Science,2(1), 183–202.

    MATH  Google Scholar 

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Correspondence to Karim H. Moussa.

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Moussa, K.H., El-Khamy, S.E. A projected fast ISTA algorithm for joint beam forming and antenna selection in massive MIMO. Wireless Netw 26, 121–127 (2020). https://doi.org/10.1007/s11276-018-1786-0

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  • DOI: https://doi.org/10.1007/s11276-018-1786-0

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