Advertisement

Energy Efficiency Maximization with Per-Antenna Power Constraints for Multicell Networks Using D.C. Programming

  • Le Ty KhanhEmail author
  • Ha Hoang Kha
  • Nguyen Minh Hoang
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 257)

Abstract

This paper studies the energy efficiency (EE) optimization problem in multicell wireless networks in which each base station (BS) equipped with multiple antennas serves multiple users at the same time and in the same frequency. The problem of interest is to design the precoders to maximize the network EE subject to practical power constraints at physical layers. The resultant optimization design problem is nonconvex fractional programming and, thus, finding its optimal solution is mathematically challenging. In this paper, we use a combination of difference of convex (d.c.) programming and the Dinkelbach algorithm to iteratively solve the optimization problem. Then, by numerical simulations, we verify the convergence characteristics of the iterative algorithm and examine the EE performance of the system as compared to an spectral efficiency (SE) approach.

Keywords

Energy efficiency Multicell Precoder design Per-antenna power constraints D.C. programming 

Notes

Acknowledgement

This research is funded by Vietnam National University HoChiMinh City (VNU-HCM) under grant number C2017-20-12.

References

  1. 1.
    Cisco: Cisco visual networking index: global mobile data traffic forcast update 2015–2020, March 2016. https://www.cisco.com/c/dam/m/en_in/innovation/enterprise/assets/mobile-white-paper-c11-520862.pdf
  2. 2.
    Sanjabi, M., Razaviyayn, M., Luo, Z.Q.: Optimal joint base station assignment and beamforming for heterogeneous networks. IEEE Trans. Sig. Process. 62, 1950–1961 (2014)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Christensen, S.S., Agarwal, R., Carvalho, E.D., Cioffi, J.M.: Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design. IEEE Trans. Wirel. Commun. 7, 4792–4799 (2008)CrossRefGoogle Scholar
  4. 4.
    Oh, D.C., Lee, H.C., Lee, Y.H.: Power control and beamforming for femtocells in the presence of channel uncertainty. IEEE Trans. Veh. Technol. 60, 2545–2554 (2011)CrossRefGoogle Scholar
  5. 5.
    Li, G.Y., et al.: Energy-efficient wireless communications: tutorial, survey, and open issues. IEEE Wirel. Commun. 18, 28–35 (2011)CrossRefGoogle Scholar
  6. 6.
    Jiang, C., Cimini, L.J.: Energy-efficient transmission for MIMO interference channels. IEEE Trans. Wirel. Commun. 12, 2988–2999 (2013)CrossRefGoogle Scholar
  7. 7.
    Huang, Y., Xu, J., Qiu, L.: Energy efficient coordinated beamforming for multi-cell MISO systems. In: IEEE Global Communication Conference GLOBECOM, pp. 2526–2531 (2013)Google Scholar
  8. 8.
    He, S., Huang, Y., Jin, S., Yu, F., Yang, L.: Max-min energy efficient beamforming for multicell multiuser joint transmission systems. IEEE Commun. Lett. 17, 1956–1959 (2013)CrossRefGoogle Scholar
  9. 9.
    Chen, Y., Zhang, S., Xu, S., Li, G.Y.: Fundamental trade-offs on green wireless networks. IEEE Commun. Mag. 49, 30–37 (2011)CrossRefGoogle Scholar
  10. 10.
    Kwon, H., Birdsall, T.: Channel capacity in bits per joule. IEEE J. Oceanic Eng. 11, 97–99 (1986)CrossRefGoogle Scholar
  11. 11.
    Verdu, S.: On channel capacity per unit cost. IEEE Trans. Inf. Theor. 36, 1019–1030 (1990)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Nguyen, V.D., Nguyen, H.V., Nguyen, C.T., Shin, O.S.: Spectral efficiency of full-duplex multi-user system: beamforming design, user grouping, and time allocation. IEEE Access 5, 5785–5797 (2017)CrossRefGoogle Scholar
  13. 13.
    Nguyen, K.-G., Tran, L.-N., Tervo, O., Vu, Q.-D., Juntti, M.: Achieving energy efficiency fairness in multicell MISO downlink. IEEE Commun. Lett. 19, 1426–1429 (2015)CrossRefGoogle Scholar
  14. 14.
    Vu, T.T., Kha, H.H., Tuan, H.D.: Transceiver design for optimizing the energy efficiency in multiuser MIMO channels. IEEE Commun. Lett. 20, 1507–1510 (2016)CrossRefGoogle Scholar
  15. 15.
    Amin, O., Bedeer, E., Ahmed, M.H., Dobre, O.A.: Energy efficiency spectral efficiency tradeoff: a multiobjective optimization approach. IEEE Trans. Veh. Technol. 65, 1975–1981 (2016)CrossRefGoogle Scholar
  16. 16.
    Sheng, Z., Tuan, H.D., Tam, H.H.M., Nguyen, H.H., Fang, Y.: Energy efficient precoding in multicell networks with full-duplex base stations. EURASIP J. Wirel. Commun. Netw. 2017(48), 13 (2017)Google Scholar
  17. 17.
    Li, Y., Fan, P., Beaulieu, N.C.: Cooperative downlink max-min energy-efficient precoding for multicell MIMO networks. IEEE Trans. Veh. Technol. 65, 9425–9430 (2016)CrossRefGoogle Scholar
  18. 18.
    Chi, P.H., Kha, H.H.: Optimized energy efficiency for multicell MIMO coopearitive systems with user rate constraints. In: 2017 International Symposium Electrical and Electronics Engineering, pp. 212–216, November 2017Google Scholar
  19. 19.
    Vu, M.: MIMO capacity with per-antenna power constraint. In: 2011 IEEE Global Telecommunications Conference (GLOBECOM), pp. 1–5, December 2011Google Scholar
  20. 20.
    Tran, L.N., Juntti, M., Bengtsson, M., Ottersten, B.: Successive zero-forcing DPC with per-antenna power constraint: optimal and suboptimal designs. In: 2012 IEEE International Conference Communications ICC, pp. 3746–3751, June 2012Google Scholar
  21. 21.
    He, S., Huang, Y., Yang, L., Ottersten, B.: Coordinated multicell multiuser precoding for maximizing weighted sum energy efficiency. IEEE Trans. Sig. Process. 62, 741–751 (2014)MathSciNetCrossRefGoogle Scholar
  22. 22.
    Kha, H.H., Tuan, H.D., Nguyen, H.H.: Fast global optimal power allocation in wireless networks by local D.C. programming. IEEE Trans. Wirel. Commun. 11, 510–515 (2012)CrossRefGoogle Scholar
  23. 23.
    Grant, M., Boyd, S.: CVX: Matlab software for disciplined convex programming, version 2.1. March 2014. http://cvxr.com/cvx
  24. 24.
    Crouzeix, J.-P., Ferland, J.A.: Algorithms for generalized fractional programming. Math. Program. 52(1), 191–207 (1991)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Hegde, G., Ramos-Cantor, O.D., Cheng, Y., Pesavento, M.: Optimal resourceblock allocation and muting in heterogeneous networks. In: 2016 IEEE International Conference Acoustics, Speech and Signal Processing (ICASSP), pp. 3581–3585, March 2016Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Le Ty Khanh
    • 1
    Email author
  • Ha Hoang Kha
    • 1
  • Nguyen Minh Hoang
    • 2
  1. 1.Ho Chi Minh City University of Technology, VNU-HCMHo Chi MinhVietnam
  2. 2.Banking University of HCM CityHo Chi MinhVietnam

Personalised recommendations