Skip to main content
Log in

Resource allocation in multicell systems with coordinated beamforming and partial data cooperation: a study on the effect of cooperation on achievable performance

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

The rise in wireless data traffic requires innovative interference management techniques to meet the demand. Transmit cooperation among multiple base stations has been proposed as a solution to this challenge and improve throughput. This paper proposes novel resource allocation algorithms with two different cooperation paradigms, viz. the cooperative beamforming and partial data cooperation. The well-known duality principle, which has been used to solve uplink and downlink optimisation problems in previous literature, is shown to exist for multicell systems with both coordinated beamforming and the novel paradigm termed as partial data cooperation. Using the generalised version of duality, this paper solves relevant resource allocation problems in both cases. The proposed power allocation problems are shown to outperform some of the existing optimisation techniques in terms of throughput while having significant conceptual and theoretical advantage.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. Analyses of full duplex communication requires modelling of the self-interference [9], which is not within the scope of this work.

  2. For broadcast systems, the channel vector is a column, hence the Hermitian is multiplied with the transmit column vector to obtain a scalar.

  3. This is different from the complexity of encoding/decoding the bits using DPC.

  4. For notational convenience, in PDC schemes we denote the total number of UE by J, unlike the CBF case.

  5. (19b) can be proved by comparing \(\mathcal {S}^{{{\mathrm{DL}}}}(l-1, k)\) and \(\mathcal {S}^{{{\mathrm{DL}}}}(l, k)\) according to the definition from (18). Similarly, (19c) can be shown by comparing \(\mathcal {S}^{{{\mathrm{DL}}}}(L, k-1)\) and \(\mathcal {S}^{{{\mathrm{DL}}}}(1, k)\).

  6. This is in contrast with Algorithm 1, where the problems are solved parallely and solutions are independent.

References

  1. Marzetta, T. L. (2010). Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Transactions on Wireless Communications, 9(11), 3590–3600.

    Article  Google Scholar 

  2. Chae, C. B., Hwang, I., Heath, R. W., & Tarokh, V. (2012). Interference aware-coordinated beamforming in a multi-cell system. IEEE Transactions on Wireless Communications, 11(10), 3692–3703.

    Article  Google Scholar 

  3. Li, Y., Bai, L., Chen, C., Jin, Y., & Choi, J. (2013). Successive orthogonal beamforming for cooperative multi-point downlinks. IET Communications, 7(8), 706–714.

    Article  Google Scholar 

  4. He, S., Huang, Y., Yang, L., Nallanathan, A., & Liu, P. (2012). A multi-cell beamforming design by uplink-downlink max–min SINR duality. IEEE Transactions on Wireless Communications, 11(8), 2858–2867.

    Google Scholar 

  5. Dartmann, G., Gong, X., Afzal, W., & Ascheid, G. (2013). On the duality of the max–min beamforming problemwith per-antenna and per-antenna-array power. IEEE Transactions on Vehicular Technology, 62(2), 606–619.

    Article  Google Scholar 

  6. Nguyen, D. H. N., & Le-Ngoc, T. (2014). Sum-rate maximization in the multicell MIMO multiple-access channel with interference coordination. IEEE Transactions on Wireless Communications, 13(1), 36–48.

    Article  MATH  Google Scholar 

  7. Vishwanath, S., Jindal, N., & Goldsmith, A. J. (2003). Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels. IEEE Transactions on Information Theory, 49(10), 2658–2668.

    Article  MathSciNet  MATH  Google Scholar 

  8. Zhang, L., Zhang, R., Liang, Y. C., Xin, Y., & Vincent Poor, H. (2012). On Gaussian MIMO BC-MAC duality with multiple transmit covariance constraints. IEEE Transactions on Information Theory, 58(4), 2064–2078.

    Article  MathSciNet  MATH  Google Scholar 

  9. Kim, S. M., & Bengtsson, M. (2016). Virtual full-duplex buffer-aided relaying in the presence of inter-relay interference. IEEE Transactions on Wireless Communications, 15(4), 2966–2980.

    Article  Google Scholar 

  10. Hwang, I., Chae, C. B., Lee, J., & Heath, R. W. (2013). Multicell cooperative systems with multiple receive antennas. IEEE Wireless Communications, 20(1), 50–58.

    Article  Google Scholar 

  11. Caire, G., & Shitz, S. S. (2003). On the achievable throughput of a multiantenna Gaussian broadcast channel. IEEE Transactions on Information Theory, 49(7), 1691–1706.

    Article  MathSciNet  MATH  Google Scholar 

  12. Kießling, M. (2004). Statistical analysis and transmit prefiltering for MIMO wireless systems in correlated fading environments. PhD thesis, Universität Stuttgart.

  13. Hoffman, K., & Kunze, R. (2001). Linear algebra (2nd ed.). New Jersey: Pearson Education Inc.

    MATH  Google Scholar 

  14. Roy, S. B., & Madhukumar, A. S. (2015). Characterising the Pareto frontier of multiple access rate region. Springer Journal of Wireless Networks, 21(5), 1537–1548.

    Article  Google Scholar 

  15. Zanella, A., Chiani, M., & Win, M. Z. (2005). MMSE reception and successive interference cancellation for MIMO systems with high spectral efficiency. IEEE Transactions on Wireless Communications, 4(3), 1244–1253.

    Article  Google Scholar 

  16. Schubert, M., & Boche, H. (2007). A generic approach to QoS-based transceiver optimization. IEEE Transactions on Communications, 55(8), 1557–1566.

    Article  Google Scholar 

  17. Barman Roy, S., Madhukumar, A. S., & Joung, J. (2017). On joint pareto frontier in multiple access and relay rate regions with Rayleigh fading. IEEE Transactions on Vehicular Technology, 66(5), 3777–3786.

    Article  Google Scholar 

  18. Berry, M. W. (1992). Large scale singular value computations. International Journal of Supercomputer Applications, 6(1), 13–49.

    Article  Google Scholar 

  19. You, L., Gao, X., Swindlehurst, A. L., & Zhong, W. (2016). Channel acquisition for massive MIMO-OFDM with adjustable phase shift pilots. IEEE Transactions on Signal Processing, 64(6), 1461–1476.

    Article  MathSciNet  MATH  Google Scholar 

  20. Colemanm, T. F., & Pothen, A. (1987). The null space problem II: Algorithms. Journal on Algebraic Discrete Methods, 8(4), 544–563.

    Article  MathSciNet  MATH  Google Scholar 

  21. Annapureddy, V. S., & Veeravalli, V. V. (2009). Gaussian interference networks: Sum capacity in the low interference regime and new outer bounds on the capacity region. IEEE Transactions on Information Theory, 55(7), 3032–3050.

    Article  MathSciNet  MATH  Google Scholar 

  22. Costa, M. (1983). Writing on dirty paper. IEEE Transactions on Information Theory, 29(3), 439–441.

    Article  MathSciNet  MATH  Google Scholar 

  23. Cheng, R. S., & Verdú, S. (1993). Gaussian multiaccess channels with ISI: Capacity region and multiuser water filling. IEEE Transactions on Information Theory, 39(3), 773–785.

    Article  MathSciNet  MATH  Google Scholar 

  24. Birkhoff, G. (1940). Lattice theory. New York: American Mathematical Society.

    MATH  Google Scholar 

  25. Boyd, S., & Vandenberghe, L. (2004). Convex optimization (2nd ed.). New York: Cambridge University Press.

    Book  MATH  Google Scholar 

  26. Roy, S. B., & Madhukumar, A. S. (2014). Resource allocation strategy in multiple access interference channel. In Proceedings of vehicular technology conference fall, Vancouver, British Columbia (pp. 1–5).

  27. Chandrasekhar, V., Andrews, J. G., Muharemovict, T., Shen, Z., & Gatherer, A. (2009). Power control in two-tier femtocell networks. IEEE Transactions on Wireless Communications, 8(8), 4316–4328.

    Article  Google Scholar 

  28. Huh, H., Papadopoulos, H. C., & Caire, G. (2010). Multiuser MIMO transmitter optimization for inter-cell interference mitigation. IEEE Transactions on Signal Processing, 58(8), 4272–4285.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This work was supported by Singapore Ministry of Education Academic Research Fund Tier 1 grant. The authors also thank the anonymous reviewers and the editor for their constructive comments and suggestions which helped us to improve the quality of the paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. Barman Roy.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Barman Roy, S., Madhukumar, A.S. & Chin, F. Resource allocation in multicell systems with coordinated beamforming and partial data cooperation: a study on the effect of cooperation on achievable performance. Wireless Netw 25, 1749–1762 (2019). https://doi.org/10.1007/s11276-017-1627-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-017-1627-6

Keywords

Navigation