# Energy-efficiency resource allocation of very large multi-user MIMO systems

- 758 Downloads
- 11 Citations

## Abstract

With increasing demand in multimedia applications and high data rate services, energy consumption of wireless devices has become a problem. At the user equipment side, high-level energy consumption brings much inconvenience, especially for mobile terminals that cannot connect an external charger, due to an exponentially increasing gap between the available and required battery capacity. Motivated by this, in this paper we consider uplink energy-efficient resource allocation in very large multi-user MIMO systems. Specifically, both the number of antenna arrays at BS and the transmit data rate at the user are adjusted to maximize the energy efficiency, in which the power consumption accounts for both transmit power and circuit power. We proposed two algorithms. Algorithm1, we demonstrate the existence of a unique globally optimal data rate and the number of antenna arrays by exploiting the properties of objective function, then we develop an iterative algorithm to obtain this optimal solution. Algorithm2, we transform the considered nonconvex optimization problem into a convex optimization problem by exploiting the properties of fractional programming, then we develop an efficient iterative resource allocation algorithm to obtain this optimal solution. Our simulation results did not only show that the the proposed two algorithms converge to the solution within a small number of iterations, but demonstrated also the performances of the proposed two algorithms are close to the optimum. Meanwhile, it also shows that with a given number iterations the performance of proposed algorithm1 is superior to proposed algorithm2 under small *p* _{ C }. On the contrary, the performance of proposed algorithm2 is superior to proposed algorithm1 under large *p* _{ C }.

## Keywords

Energy efficiency Multi-user MIMO## Notes

### Acknowledgments

This work was supported by National Science and Technology Major Project of China under Grant 2013ZX03003006-002, National Natural Science Foundation of China under Grants 61271018, 61201176 and 61372101, Research Project of Jiangsu Province under Grants BK20130019, BK2011597, and BE2012167, Program for New Century Excellent Talents in University under Grant NCET-11-0088.

## References

- 1.Xiong, C., Li, G. Y., Zhang, S. Q., Yan, C., & Xu, S. G. (2012). Energy-efficient resource allocation in OFDMA networks.
*IEEE Transaction on Communications, 60*(12):3767–3778.CrossRefGoogle Scholar - 2.Zhong, C. X., & Yang, L. X. (2007). User schedling and power allocation for downlink of MIMO systems with limited feedback.
*International Workshop on Cross Layer Design*, pp. 10–13.Google Scholar - 3.Zhong, C. X., Li, C. G., Zhao, R., Yang, L. X., & Gao, X. Q. (2009). Dynamic resource allocation for downlink multi-user MIMO-OFDMA/SDMA systems. In
*Proceedings of IEEE international conference on communications*, pp. 1826–1830.Google Scholar - 4.Akbari, A., Hoshyar, R., & Tafazolli, R. (2010). Energy-efficient resource allocation in wireless OFDMA systems. In
*IEEE international symposium on personal, indoor and mobile radio communications*, pp. 1731–1735.Google Scholar - 5.Miao, G. W., Himayat, N., Li, G. Y., & Bormann, D. (2008). Energy-efficient design in wireless OFDMA. In
*IEEE international conference on communications*, pp. 3307–3312.Google Scholar - 6.Miao, G. W., Himayat, N., Li, G. Y., & Talwar, S. (2009). Low-complexity energy-efficient OFDMA.
*IEEE international conference on communications*, pp. 1–5.Google Scholar - 7.Miao, G. W., Himayat, N., Li, G. Y., Koc, A. T., & Talwar, S. (2009). Interference-aware energy-efficient power optimization. In
*IEEE international conference on communications*.Google Scholar - 8.Miao, G. W., Himayat, N., Li, G. Y., & Swami, A. (2009). Cross-layer optimization for energy-efficient wireless communications: A survey.
*Wireless Communications and Mobile Computing, 9*(4), 529–542.CrossRefGoogle Scholar - 9.Miao, G. W., Himayat, N., & Li, G. Y. (2010). Energy-efficient link adaptation in frequency-selective channels.
*IEEE Transaction Communications, 58*(2), 545–554.CrossRefGoogle Scholar - 10.Miao, G. W., Himayat, N., Li, G. Y., & Talwar, S. (2011). Distributed interference-aware energy-efficient power optimization.
*IEEE Transaction Communications, 10*(4), 1323–1333.CrossRefGoogle Scholar - 11.Hu, Y., Huang, Y. M., & Yang, L. X. (2011). Energy-efficient resource allocation in multi-user OFDMA systems. In
*2011 International conference on wireless communications and signal processing*.Google Scholar - 12.Hu, Y., Xu, D. F., Ji, B. F., Huang, Y. M., & Yang, L. X. (2012). Energy-efficient of very large multi-user MIMO systems. In
*2012 International conference on wireless communications and signal processing*.Google Scholar - 13.Andreev, S., Koucheryavy, Y., Himayat, N., Gonchukov, P., & Turlikov, A. (2010). Active-mode power optimization in OFDMA-based wireless networks.
*IEEE Globecom Workshops*, pp. 799–803.Google Scholar - 14.Ng, D. W. K., Lo, E. S., & Schober, R. (2012) Energy-efficient resource allocation for secure OFDMA systems.
*IEEE Transaction on Vehicle Technology, 61*(6), 2572–2585.CrossRefGoogle Scholar - 15.Ng, D. W. K., Lo, E. S., & Schober, R. (2012) Energy-efficient resource allocation in OFDMA systems with large numbers of base station antennas.
*IEEE Transactions on Wireless Communications, 11*(9), 3292–3304.CrossRefGoogle Scholar - 16.Rusek, F., Persson, D., Lau, B. K. et al. (2012). Scaling up MIMO: Opportunities and challenges with very large arrays.
*CNSR’09, Canada New Brunswick*, arXiv:1201.3210v1[cs.IT] 16 Jan.Google Scholar - 17.Huang, Y. M., Zheng, G., Bengtsson, M. et. al (2011). Distributed multicell beamforming design with limited intercell coordination.
*IEEE Transactions on Signal Processing, 59*(2), 728–738.CrossRefMathSciNetGoogle Scholar - 18.Huang, Y. M., Yang, L. X., & Bengtsson, M. et al. (2010). A limited feedback joint precoding for amplify-and-forward relaying.
*IEEE Transactions on Signal Processng, 58*(3), 1347–1357.CrossRefMathSciNetGoogle Scholar - 19.Miao, G. W., & Zhang J. Z. (2011). On optimal energy-efficient multi-user MIMO.
*2011 IEEE global telecommunications conference*, pp. 4620–4628.Google Scholar - 20.Huang, Y. M., Zheng, G., & Bengtsson, M. et al. (2012). Distributed multicell beamforming design approaching pareto boundary with max–min fairness.
*IEEE Transactions on Wireless Communications, 11*(8), 2921–2930.Google Scholar - 21.Ji, B. F., Song, K., & Huang, Y. M. et al. (2013). A cooperative relay selection for two-way cooperative relay networks in Nakagami channels.
*Wireless Personal Communications, 71*(3), 2045–2065.CrossRefGoogle Scholar - 22.Ngo, H. Q., Larsson, E. G., & Marzetta, T. L. (2013). Energy and spectral efficiency of very large multiuser MIMO systems.
*IEEE Transaction on Communications, 61*(4), 1436–1449.CrossRefGoogle Scholar - 23.Li, G. Y., Xu, Z. K., & Xiong, C. et al. (2011). Energy-efficient wireless communications: Tutorial, survey, and open issues.
*IEEE Transaction on Wireless Communications*, 28–34.Google Scholar - 24.Cui, S. G., Goldsmith, A. J., & Bahai, A. (2004). Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks.
*IEEE Journal on Selected Areas in Communications, 22*(6), 1086–1098.CrossRefGoogle Scholar - 25.Dinkelbach, W. (1967). On nonlinear fractional programming.
*Management Science, 13*, 492–498.CrossRefzbMATHMathSciNetGoogle Scholar