ETRI Journal

Electronics and Telecommunications Research Institute (한국전자통신연구원)
권호 표지
DOI QR코드

DOI QR Code

Low complexity ordered successive interference cancelation detection algorithm for uplink MIMO SC-FDMA system

  • Nalamani G. Praveena (Department of Electronics and Communication Engineering, R.M.K. College of Engineering and Technology) ;
  • Kandasamy Selvaraj (Department of Information Technology, PSNA College of Engineering) ;
  • David Judson (Department of Electronics and Communication Engineering, St. Xavier's Catholic College of Engineering) ;
  • Mahalingam Anandaraj (Department of Information Technology, PSNA College of Engineering)
  • Received : 2022.04.10
  • Accepted : 2022.08.07
  • Published : 2023.10.20
Download PDF
⟨ Previous Next ⟩

Abstract

In mobile communication, the most exploratory technology of fifth generation is massive multiple input multiple output (MIMO). The minimum mean square error and zero forcing based linear detectors are used in multiuser detection for MIMO single-carrier frequency division multiple access (SCFDMA). When the received signal is detected and regularization sequence is joined in the equalization of spectral null amplification, these schemes experience an error performance and the signal detection assesses an inversion of a matrix computation that grows into complexity. Ordered successive interference cancelation (OSIC) detection is considered for MIMO SC-FDMA, which uses a posteriori information to eradicate these problems in a realistic environment. To cancel the interference, sorting is preferred based on signal-to-noise ratio and log-likelihood ratio. The distinctiveness of the methodology is to predict the symbol with the lowest error probability. The proposed work is compared with the existing methods, and simulation results prove that the defined algorithm outperforms conventional detection methods and accomplishes better performance with lower complication.

Keywords

References

  1. Z. Lin, P. Xiao, B. Vucetic, and M. Sellathurai, Analysis of receiver algorithms for LTE SC-FDMA based uplink MIMO systems, IEEE Trans. Wireless Commun. 9 (2010), 60-65. https://doi.org/10.1109/TWC.2010.01.090199
  2. S. Okuyama, K. Takeda, and F. Adachi, Iterative MMSE detection and interference cancellation for uplink SC-FDMA MIMO using HARQ, (Proc. IEEE International Conference on Communications, Kyoto, Japan), 2011, pp. 1-5.
  3. E. Dahlman, S. Parkvall, and J. Skold, 4G: LTE/LTE-advanced for mobile broadband, Academic, San Diego, CA, USA, 2011.
  4. S. Sun, J. Hu, Y. Peng, X. Pan, L. Zhao, and J. Fang, Support for vehicle-to-everything services based on LTE, IEEE Wireless Commun. 23 (2016), 4-8.
  5. F. S. Al-kamali, M. I. Dessouky, B. M. Sallam, and F. E. Abd El-Samie, Regularized MIMO equalization for SC-FDMA systems, Circ. Syst. Signal Process. 31 (2012), 1423-1441. https://doi.org/10.1007/s00034-011-9382-x
  6. K. Selvaraj, P. Ganeshkumar, and M. Anandaraj, Iterative MMSE equalization and CFO compensation for the uplink SCFDMA transmission, Int. J. Commun. Syst. 29 (2016), 1323-1337. https://doi.org/10.1002/dac.3103
  7. H. Noh, M. Kim, J. Ham, and C. Lee, A practical MMSE-ML detector for a MIMO SC-FDMA system, IEEE Commun. Lett. 13 (2009), 902-904. https://doi.org/10.1109/LCOMM.2009.12.091709
  8. D. Jeong and J. Kim, Signal detection for MIMO SC-FDMA systems exploiting block circulant channel structure, IEEE Trans. Veh. Technol. 65 (2016), 7774-7779. https://doi.org/10.1109/TVT.2015.2485264
  9. M. Mandloi and V. Bhatia, Low-complexity near-optimal iterative sequential detection for uplink massive MIMO systems, IEEE Commun. Lett. 21 (2017), 568-571. https://doi.org/10.1109/LCOMM.2016.2637366
  10. K. Selvaraj, D. Judson, P. Ganeshkumar, and M. Anandaraj, Low complexity linear detection for multiuser MIMO SC-FDMA uplink system, Wireless Personal Commun. 98 (2020), 1587-1603.
  11. A. Elghariani and M. Zoltowski, Low complexity detection algorithms in large-scale MIMO systems, IEEE Trans. Wireless Commun. 15 (2016), 1689-1702.
  12. D. Judson and V. Bhaskar, Error rate analysis of SIMO-CDMA with complementary codes under multipath fading channels, Wireless Personal Commun. 98 (2018), 1663-1677. https://doi.org/10.1007/s11277-017-4938-0
  13. P. Ganeshkumar, K. Selvaraj, M. Anandraj, and K. P. Vijayakumar, Iterative nonlinear detection for SFBC SC-FDMA uplink MIMO transmission systems, Int. J. Commun. Syst. 29 (2016), 1568-1581. https://doi.org/10.1002/dac.3136
  14. D. Judson, V. Bhaskar, and K. Selvaraj, Pre-equalization schemes for MIMO CC-CDMA systems over frequency-selective fading channels, Wireless Personal Commun. 98 (2018), 1587-1603. https://doi.org/10.1007/s11277-017-4936-2
  15. B. Dhivagar, K. Kuchi, and K. Giridhar, An iterative DFE receiver for MIMO SC- FDMA uplink, IEEE Commun. Lett. 18 (2014), 2141-2144. https://doi.org/10.1109/LCOMM.2014.2361787
  16. Y. Shang and X. Xia, An Improved Fast Recursive Algorithm for V-BLAST with Optimal Ordered Detections, (IEEE International Conference on Communications, China), 2008, pp. 756-760.
  17. K. Selvaraj, M. Anandaraj, K. Ramesh, and R. Krishnan, Iterative SIC algorithm based detection for multiuser MIMO SCFDMA uplink system, Mater. Today: Proc. (2021). https://doi.org/10.1016/j.matpr.2021.02.190
  18. F. Jiang and C. Li, Soft Input Soft Output MMSE-SQRD Based Turbo Equalization for MIMO-OFDM Systems under Imperfect Channel Estimation, (IEEE Global Communications Conference, SanDiego, CA, USA), 2015, pp. 1-6.
  19. F. Jiang, Y. Zhang, and C. Li, A new SQRD-based soft interference cancelation scheme in multi-user MIMO SC-FDMA system, IEEE Commun. Lett. 21 (2017), 821-824. https://doi.org/10.1109/LCOMM.2016.2642189
  20. S. Chen, W. Wang, S. Jin and X. Gao, Sorted QR Decomposition Based Detection for MU-MIMO LTE Uplink, (IEEE 71st Vehicular Technology Conference, Taipei, Taiwan), 2010, pp. 1-5.
  21. M. Mandloi and V. Bhatia, Ordered iterative successive interference cancellation algorithm for large MIMO detection, (IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, Kozhikode, India), 2015, pp. 1-5.
  22. J. Wang, O. Y. Wen and S. Li, Soft-output MMSE OSIC MIMO detector with reduced-complexity approximations, (IEEE 8th Workshop on Signal Processing Advances in Wireless Communications, Helsinki, Finland), 2007, pp. 1-5.
  23. A. Riadi, M. Boulouird, and M. M'Rabet Hassani, Performances of OSIC detector of an uplink OFDM massive MIMO system in Rayleigh and Rican fading channels, Wireless Personal Commun. 98 (2020), 1663-1677.
  24. E. Vlachos, A. S. Lalos, and K. Berberidis, Low-complexity OSIC equalization for OFDM-based vehicular communications, IEEE Trans. Veh. Technol. 66 (2017), 3765-3776.
  25. Spatial channel model for multiple input multiple output (MIMO) simulations, 3GPP, vol. TR 25.996, v. 10.0.0, Apr. 2011.
  26. Evolved universal terrestrial radio access (LTE); User equipment (UE) radio transmission and reception, Sophia-Antipolis Cedex, France, 3GPP TS 36.101, Jul. 2013.