Likelihood ascent search detection for coded massive MU-MIMO systems to mitigate IAI and MUI

Authors

DOI:

https://doi.org/10.3103/S0735272720050015

Keywords:

massive multiuser MIMO, inter-antenna interference, IAI, multiuser interference, MUI, singular value decomposition, multiuser detection, likelihood ascent search

Abstract

The main aim of massive multiuser multiple-input multiple-output (MU-MIMO) system is to improve the throughput and spectral efficiency in 5G wireless networks. The performance of MU-MIMO system is severely influenced by inter-antenna interference (IAI) and multiuser interference (MUI). The IAI occurs due to space limitations at each user terminal (UT) and the MUI is added when one UT is in the vicinity of another UT in the same cellular network. IAI can be mitigated through a precoding scheme such as singular value decomposition (SVD), and MUI is suppressed by an efficient multiuser detection (MUD) schemes. The maximum likelihood (ML) detector has optimal performance; however, it has a highly complex structure and involves the need of a large number of computations especially in massive structures. Thus, the neighborhood search-based algorithm such as likelihood ascent search (LAS) has been found to be a better alternative for mitigation of MUI as it results in near optimal performance with low complexity. Most of the recent papers are aimed at eliminating either MUI or IAI, whereas the proposed work presents joint SVD precoding and LAS MUD to mitigate both IAI and MUI. The proposed scheme can achieve a near-optimal performance with smaller number of matrix computations.

Author Biography

Kalapraveen Bagadi, VIT University, Vellore

School of Electronics Engineering

References

A. Chockalingam and B. Sundar Rajan, Large MIMO systems, vol. 9781107026. Cambridge University Press, 2011, doi: https://doi.org/10.1017/CBO9781139208437.

E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, “Massive MIMO for next generation wireless systems,” IEEE Commun. Mag., vol. 52, no. 2, pp. 186–195, 2014, doi: https://doi.org/10.1109/MCOM.2014.6736761.

L. Lu, G. Y. Li, A. L. Swindlehurst, A. Ashikhmin, and R. Zhang, “An overview of massive MIMO: Benefits and challenges,” IEEE J. Sel. Top. Signal Process., vol. 8, no. 5, pp. 742–758, 2014, doi: https://doi.org/10.1109/JSTSP.2014.2317671.

E. Biglieri, R. Calderbank, A. Constantinides, A. Goldsmith, A. Paulraj, and H. V. Poor, MIMO Wireless Communications, vol. 9780521873. Cambridge University Press, 2007, doi: https://doi.org/10.1017/CBO9780511618420.

Y. Liu, J. Liu, Q. Wu, Y. Zhang, and M. Jin, “A Near-Optimal Iterative Linear Precoding with Low Complexity for Massive MIMO Systems,” IEEE Commun. Lett., vol. 23, no. 6, pp. 1105–1108, 2019, doi: https://doi.org/10.1109/LCOMM.2019.2911472.

C. Tang, Y. Tao, Y. Chen, C. Liu, L. Yuan, and Z. Xing, “Approximate iteration detection and precoding in massive MIMO,” China Commun., vol. 15, no. 5, pp. 183–196, 2018, doi: https://doi.org/10.1109/CC.2018.8387997.

N. Fatema, G. Hua, Y. Xiang, D. Peng, and I. Natgunanathan, “Massive MIMO Linear Precoding: A Survey,” IEEE Syst. J., vol. 12, no. 4, pp. 3920–3931, 2018, doi: https://doi.org/10.1109/JSYST.2017.2776401.

V. V. Gudla and V. B. Kumaravelu, “Dynamic spatial modulation for next generation networks,” Phys. Commun., vol. 34, pp. 90–104, 2019, doi: https://doi.org/10.1016/j.phycom.2019.03.002.

N. R. Challa and K. Bagadi, “Design of near-optimal local likelihood search-based detection algorithm for coded large-scale MU-MIMO system,” Int. J. Commun. Syst., p. e4436, 2020, doi: https://doi.org/10.1002/dac.4436.

M. Al-Rawi and M. Al-Rawi, “Performance of massive MIMO uplink system over Nakagami-m fading channel,” Radioelectron. Commun. Syst., vol. 60, no. 1, pp. 13–17, 2017, doi: https://doi.org/10.3103/S0735272717010022.

T. A. Sheikh, J. Bora, and M. A. Hussain, “Sum-Rate Performance of Massive MIMO Systems in Highly Scattering Channel with Semi-Orthogonal and Random User Selection,” Radioelectron. Commun. Syst., vol. 61, no. 12, pp. 547–555, 2018, doi: https://doi.org/10.3103/S0735272718120026.

A. H. Mehana and A. Nosratinia, “Diversity of MIMO linear precoding,” IEEE Trans. Inf. Theory, vol. 60, no. 2, pp. 1019–1038, 2014, doi: https://doi.org/10.1109/TIT.2013.2289860.

K. P. Bagadi, V. Annepu, and S. Das, “Recent trends in multiuser detection techniques for SDMA–OFDM communication system,” Phys. Commun., vol. 20, pp. 93–108, 2016, doi: https://doi.org/10.1016/j.phycom.2016.07.001.

D. Lee, “Performance analysis of zero-forcing-precoded scheduling system with adaptive modulation for multiuser-multiple input multiple output transmission,” IET Commun., vol. 9, no. 16, pp. 2007–2012, 2015, doi: https://doi.org/10.1049/iet-com.2015.0201.

X. He, Q. Guo, J. Tong, J. Xi, and Y. Yu, “Low-complexity approximate iterative LMMSE detection for large-scale MIMO systems,” Digit. Signal Process. A Rev. J., vol. 60, pp. 134–139, 2017, doi: https://doi.org/10.1016/j.dsp.2016.09.004.

A. Liu and V. K. N. Lau, “Two-stage constant-envelope precoding for low-cost massive MIMO systems,” IEEE Trans. Signal Process., vol. 64, no. 2, pp. 485–494, 2016, doi: https://doi.org/10.1109/TSP.2015.2486749.

A. Hindy and A. Nosratinia, “Ergodic Fading MIMO Dirty Paper and Broadcast Channels: Capacity Bounds and Lattice Strategies,” IEEE Trans. Wirel. Commun., vol. 16, no. 8, pp. 5525–5536, 2017, doi: https://doi.org/10.1109/TWC.2017.2712631.

I. W. Lai et al., “Spatial Permutation Modulation for Multiple-Input Multiple-Output (MIMO) Systems,” IEEE Access, vol. 7, pp. 68206–68218, 2019, doi: https://doi.org/10.1109/ACCESS.2019.2918710.

L. Gopal, Y. Rong, and Z. Zang, “Tomlinson-Harashima Precoding Based Transceiver Design for MIMO Relay Systems With Channel Covariance Information,” IEEE Trans. Wirel. Commun., vol. 14, no. 10, pp. 5513–5525, 2015, doi: https://doi.org/10.1109/TWC.2015.2439279.

R. Masashi Fukuda and T. Abrao, “Linear, Quadratic, and Semidefinite Programming Massive MIMO Detectors: Reliability and Complexity,” IEEE Access, vol. 7, pp. 29506–29519, 2019, doi: https://doi.org/10.1109/ACCESS.2019.2902521.

W. A. Shehab and Z. Al-Qudah, “Singular value decomposition: Principles and applications in multiple input multiple output communication system,” Int. J. Comput. Networks Commun., vol. 9, no. 1, pp. 13–21, 2017, doi: https://doi.org/10.5121/ijcnc.2017.9102.

W. Liu, L. L. Yang, and L. Hanzo, “SVD-assisted multiuser transmitter and multiuser detector design for MIMO systems,” IEEE Trans. Veh. Technol., vol. 58, no. 2, pp. 1016–1021, 2009, doi: https://doi.org/10.1109/TVT.2008.927728.

A. Elghariani and M. Zoltowski, “Low Complexity Detection Algorithms in Large-Scale MIMO Systems,” IEEE Trans. Wirel. Commun., vol. 15, no. 3, pp. 1689–1702, 2016, doi: https://doi.org/10.1109/TWC.2015.2495163.

Y. Li, Q. He, and R. S. Blum, “Limited-Complexity Receiver Design for Passive/Active MIMO Radar Detection,” IEEE Trans. Signal Process., vol. 67, no. 12, pp. 3258–3271, 2019, doi: https://doi.org/10.1109/TSP.2019.2911262.

D. C. Araújo, T. Maksymyuk, A. L. F. de Almeida, T. Maciel, J. C. M. Mota, and M. Jo, “Massive MIMO: Survey and future research topics,” IET Commun., vol. 10, no. 15, pp. 1938–1946, 2016, doi: https://doi.org/10.1049/iet-com.2015.1091.

M. Mandloi and V. Bhatia, “Error Recovery Based Low-Complexity Detection for Uplink Massive MIMO Systems,” IEEE Wirel. Commun. Lett., vol. 6, no. 3, pp. 302–305, 2017, doi: https://doi.org/10.1109/LWC.2017.2677905.

K. V. Vardhan, S. K. Mohammed, A. Chockalingam, and B. S. Rajan, “A low-complexity detector for large MIMO systems and multicarrier CDMA systems,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 473–485, 2008, doi: https://doi.org/10.1109/JSAC.2008.080406.

P. Li and R. D. Murch, “Multiple output selection-LAS algorithm in large MIMO systems,” IEEE Commun. Lett., vol. 14, no. 5, pp. 399–401, 2010, doi: https://doi.org/10.1109/LCOMM.2010.05.100092.

S. Agarwal, A. K. Sah, and A. K. Chaturvedi, “Likelihood-Based Tree Search for Low Complexity Detection in Large MIMO Systems,” IEEE Wirel. Commun. Lett., vol. 6, no. 4, pp. 450–453, 2017, doi: https://doi.org/10.1109/LWC.2017.2702639.

A. K. Sah and A. K. Chaturvedi, “An Unconstrained Likelihood Ascent Based Detection Algorithm for Large MIMO Systems,” IEEE Trans. Wirel. Commun., vol. 16, no. 4, pp. 2262–2273, 2017, doi: https://doi.org/10.1109/TWC.2017.2661283.

L. Li, W. Meng, and C. Li, “Semidefinite further relaxation on likelihood ascent search detection algorithm for high-order modulation in massive MIMO system,” IET Commun., vol. 11, no. 6, pp. 801–808, 2017, doi: https://doi.org/10.1049/iet-com.2016.1160.

M. Chaudhary, N. K. Meena, and R. S. Kshetrimayum, “Local search based near optimal low complexity detection for large MIMO System,” in 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2016, 2017, doi: https://doi.org/10.1109/ANTS.2016.7947792.

A. K. Sah and A. K. Chaturvedi, “Sequential and Global Likelihood Ascent Search-Based Detection in Large MIMO Systems,” IEEE Trans. Commun., vol. 66, no. 2, pp. 713–725, 2018, doi: https://doi.org/10.1109/TCOMM.2017.2761383.

D. A. Pokamestov, Y. V. Kryukov, E. V. Rogozhnikov, R. R. Abenov, and A. Y. Demidov, “Concepts of the physical level of the fifth generation communications systems,” Radioelectron. Commun. Syst., vol. 60, no. 7, pp. 285–296, 2017, doi: https://doi.org/10.3103/S0735272717070019.

N. R. Challa and K. Bagadi, “Lattice Reduction Assisted Likelihood Ascent Search Algorithm for Multiuser Detection in Massive MIMO System,” in INDICON 2018 - 15th IEEE India Council International Conference, 2018, doi: https://doi.org/10.1109/INDICON45594.2018.8987139.

Published

2020-07-22

Issue

Section

Research Articles