1Department of Electrical Engineering, Da-Yeh University, Changhua, Taiwan 515, R.O.C.
Received:
May 25, 2018
Accepted:
December 4, 2018
Publication Date:
June 1, 2019
Download Citation:
||https://doi.org/10.6180/jase.201906_22(2).0017
ABSTRACT
This paper considers multiuser multiple-input multiple-output (MU-MIMO) wireless communications in which the cellular base station (BS) is equipped with a very large number of antennas. We consider time-division duplexing (TDD) scheme, in which reciprocity between uplink and downlink channels can be assumed.Benefited from the asymptotic orthogonality between channel vectors in massive MIMO, we propose an eigenvalue decomposition (EVD) based blind channel estimation algorithm from the received data during uplink transmission.Though the estimated channel vector remains scalar multiplicative ambiguity, we mitigate the ambiguity by exploiting DPSK modulation and non coherent demodulation. In the downlink, we propose a space division multiple access (SDMA) based resource allocation algorithm. As the green radio is essential in 5G and future network, energy efficiency becomes the major concern. In this paper, we evaluate system performance by the number of reliable bits transmitted per joule of energy consumed in a wireless cellular network. Numerical results verify the effectiveness of the channel estimation algorithm.
Keywords:
Eigenvalue Decomposition (EVD), Multiuser Multiple-input Multiple-output (MUMIMO), Orthogonal Frequency-division Multiple-access (OFDMA), Massive MIMO, Time-division Duplexing (TDD)
REFERENCES
- [1] Andrews, J. G., S. Buzzi, W. Choi, S. V. Hanly, A. Lozano, C. K. Soong, and J. C. Zhang (2014) What will 5G be? IEEE Journal on Selected Areas in Communications 32(6), 10651081. doi: 10.1109/JSAC. 2014.2328098
- [2] I, C. L., C. Rowell, S. Han, Z. Xu, G. Li, and Z. Pan (2014) Toward green and soft: a 5G perspective, IEEE Communications Magazine 52(2), 6673. doi: 10. 1109/MCOM.2014.6736745
- [3] Lu, L., Y. Li, A. Lee, A. Ashikhmin, and R. Zhang (2014) An overview of massive MIMO: benefits and challenges, IEEE Journal on Selected Areas in Communications 8(5), 742758. doi: 10.1109/JSTSP.2014. 2317671
- [4] Fernandes, F., A. Ashikhmin, and T. L. Marzetta (2013) Inter-cell interference in non cooperative TDD large scale antenna systems, IEEE Journal on Selected Areas in Communications 31(2), 110.
- [5] Rusek, F., D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors, and F. Tufvesson (2013) Scaling up MIMO: opportunities and challenges with very large arrays, IEEE Signal Process. Mag. 30(1), 4060. doi: 10.1109/MSP.2011.2178495
- [6] Chen, Y., S. Zhang, S. Xu, and G. Y. Li (2011) Fundamental tradeoffs on green wireless networks, IEEE Commun. Mag. 49(6), 30–37. doi: 10.1109/MCOM. 2011.5783982
- [7] Marzetta, T. L. (2010) Noncooperative cellular wireless with unlimited numbers of base station antennas, IEEE Trans. Wireless Commun. 9(11), 3590–3600. doi: 10.1109/TWC.2010.092810.091092
- [8] Wu, W. C., and C. Y. Hsu (2017) Subcarriers-and-bits allocation algorithms for downlink OFDMA-based MIMO systems, Journal of the Franklin Institute 354(11), 4615–4636. doi: 10.1016/j.jfranklin.2017.04. 019
- [9] Svedman, P., S. K. Wilson, L. J. Cimini, and B. Ottersten (2007) Opportunistic beamforming and scheduling for OFDMA systems, IEEE Trans. on Communications 55(5), 941952.
- [10] Zhang, Y. J., and K. B. Letaief (2004) Multiuser adaptive subcarrier-and-bit allocation with adaptive cell selection for OFDM systems, IEEE Trans. Wireless Communications 3(5), 15661575. doi: 10.1109/TWC. 2004.833501 \
- [11] Ashikhmin, A., and T. L. Marzetta (2012) Pilot contamination precoding in multi-cell large scale antenna systems, 2012 IEEE International Symposium on Information Theory Proceedings, Cambridge, MA, USA, 1137–1141. doi: 10.1109/ISIT.2012.6283031
- [12] Jose, J., A. Ashikhmin, T. L. Marzetta, and S. Vishwanath (2011) Pilot contamination and precoding in multi-cell TDD systems, IEEE Trans. Wireless Commun. 10(8), 2640–2651. doi: 10.1109/TWC.2011. 060711.101155
- [13] Ngo, H. Q., and E. G. Larsson (2012) EVD-based channel estimations for multicell multiuser MIMO with very large antenna arrays, Proceedings of the IEEE International Conference on Acoustics, Speed and Signal Processing (ICASSP), Kyoto, Japan. doi: 10.1109/ ICASSP.2012.6288608
- [14] Xu, F., Y. Xiao, and D. Wang (2014) Adaptive semiblind channel estimation for massive MIMO system, 2014 12th International Conference on Signal Processing (ICSP), 1923.
- [15] Mawatwal, K., D. Sen, and R. Roy (2017) A semiblind channel estimation algorithm for massive MIMO systems,IEEE Wireless Commun. Letters 6(1), 7073. doi: 10.1109/LWC.2016.2631535
- [16] Nayebi, E., and B. D. Rao (2018) Semi-blind channel estimation for multiuser massive MIMO systems, IEEE Trans. on Signal Process. 66(2), 540553. doi: 10. 1109/TSP.2017.2771725
- [17] Lozano, A., A. M. Tulino, and S. Verdú (2008) Optimum power allocation for multiuser OFDM with arbitrary signal constellations, IEEE Trans. on Communications 56(5), 828837. doi: 10.1109/TCOMM.2008. 060211
- [18] Wong, I. C., Z. Shen, B. L. Evans, and J. G. Andrews (2004) A low complexity algorithm for proportional resource allocation in OFDMA systems, 2004 IEEE Workshop on Signal Processing Systems (SIPS). doi: 10.1109/SIPS.2004.1363015
- [19] Jang, J., and K. B. Lee (2003) Transmit power adaptation for multiuser OFDM systems, IEEE Journal on Selected Areas in Communications 21(2), 828837. doi: 10.1109/JSAC.2002.807348
- [20] Haykin, S. (2001) Communication Systems, Chap. 6, 4th editions, John Wiley & Sons, Inc.
- [21] Meshkati, F., H. V. Poor, S. C. Schwart, and N. B. Mandayam (2005) An energy-efficient approach to power control and receiver design in wireless data networks, IEEE Trans. on Communications 53(11), 1885 1894. doi: 10.1109/TCOMM.2005.858695
