Research on Beamforming Algorithm for Group Scenario in Broadband Trunking System Downlink

  • Chengwen Zhang
  • Xuanhong Yan
  • Shizeng Guo
  • Chenguang He
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)


In recent years, broadband trunking system has attracted much attention as its high rate, which can replace narrow band trunking system in private network. Beamforming technology, developed from smart antenna technology, sending the signal precoding processing, can effectively improve the system’s energy efficiency. In this paper, the multicast beamforming algorithm based on the group user CSI is proposed to improve the energy efficiency of the system. Multi-user beamforming technology can improve the energy efficiency of BSs in group scenarios of broadband Trunking system, and guarantee the QoS of group users. The two optimization problems are both NP-hard. The paper adopts SDR, dropping some constraints in the original optimization problem, transform the original optimization problem into SDP to achieve the approximation solution. The improved algorithm guarantees the QoS of the group users by changing the priority of the user. Multi-user beamforming technology can improve the energy efficiency of base stations in group scenarios of broadband Trunking system, and guarantee the QoS of group users.


Broadband trunking system Group scenario Beamforming Semidefinite relaxation 



This work is supported by the National Science and Technology Major Specific Projects of China (Grant No. 2015ZX03004002-004).


  1. 1.
    Larsson, E.G., Edfors, O., Tufvesson, F., Marzetta, T.L.: Massive mimo for next generation wireless systems. IEEE Commun. Mag. 52(2), 186–195 (2014)Google Scholar
  2. 2.
    Wang, A.Y., Hur, S., Park, Y., Choi, J.H.: Efficient user selection algorithms for multiuser mimo systems with zero-forcing dirty paper coding. J. Commun. Netw. 13(3), 232–239 (2011)Google Scholar
  3. 3.
    Shenouda, M.B., Davidson, T.N.: Convex conic formulations of robust downlink precoder designs with quality of service constraints. IEEE J. Sel. Top. Sig. Process. 1(4), 714–724 (2007)Google Scholar
  4. 4.
    Benkhelifa, F., Tall, A., Rezki, Z., Alouini, M.S.: On the low SNR capacity of mimo fading channels with imperfect channel state information. IEEE Trans. Commun. 62(6), 1921–1930 (2014)Google Scholar
  5. 5.
    Gong, Q., Chen, Z., Wei, G.: Downlink multicasting beamforming with imperfect CSI on both transceiver sides.In: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1472–1477. IEEE (2012)Google Scholar
  6. 6.
    Khojastepour, M.A., Salehi-Golsefidi, A., Rangarajan, S.: Towards an optimal beamforming algorithm for physical layer multicasting. In: Information Theory Workshop, pp. 395–399. IEEE (2011)Google Scholar
  7. 7.
    Tseng, P.: Further results on approximating nonconvex quadratic optimization by semi definite programming relaxation 14(1), 268–283 (2001)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Harbin Institute of TechnologyHarbinChina

Personalised recommendations