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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Hybrid SNR-Adaptive Multiuser Detectors for SDMA-OFDM Systems

  • Yesilyurt, Ugur (Department of Electrical and Electronics Engineering, Gazi University) ;
  • Ertug, Ozgur (Department of Electrical and Electronics Engineering, Gazi University)
  • Received : 2017.08.05
  • Accepted : 2018.01.25
  • Published : 2018.04.01
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Abstract

Multiuser detection (MUD) and channel estimation techniques in space-division multiple-access aided orthogonal frequency-division multiplexing systems recently has received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean-squared error (MMSE) MUD exhibits poor performance, although it achieves lower computational complexity. With almost the same complexity, an MMSE with successive interference cancellation (SIC) scheme achieves a better bit error rate performance than a linear MMSE multiuser detector. In this paper, hybrid ML-MMSE with SIC adaptive multiuser detection based on the joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method achieves good performance close to the optimal ML performance at low SNR values and a low computational complexity at high SNR values.

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References

  1. M. Alansi, I. Elshafiye, and A. Al-Sanie, "Multiuser Detection for SDMA-OFDM Communication Systems," Electron., Commun. Photon. Conf. (SIECPC), Riyadh, Saudi Arabia, Apr. 24-26, 2011, pp. 1-5.
  2. K.P. Bagadi and S. Das, "Neural Network-Based Multiuser Detection for SDMA-OFDM System Over IEEE 802.11n Indoor Wireless Local Area Network Channel Models," Int. J. Electron., vol. 100, no. 10, Nov. 2012, pp. 1332-1347. https://doi.org/10.1080/00207217.2012.743085
  3. K.P. Bagadi, "On Development of Some Soft Computing Based Multiuser Detection Techniques for SDMA-OFDM Wireless Communication System," Ph.D. dissertation, Dept. Elect. Eng., National Institute of Technology Rourkela, India, 2014.
  4. B.K. Praveen and S. Das, "Neural Network Based Multiuser Detection Techniques in SDMA-OFDM System," in Proc. Annu. IEEE India Conf. (INDICON), Hyderabad, India, Dec 16-18, 2011, pp. 1-4.
  5. J. Zhang, S. Chen, X. Mu, and L. Hanzo, "Joint Channel Estimation and Multiuser Detection for SDMA/OFDM Based on Dual Repeated Weighted Boosting Search," IEEE Trans. Veh. Technol., vol. 60, no. 7, Sept. 2011, pp. 3265-3275. https://doi.org/10.1109/TVT.2011.2161356
  6. B.K. Praveen and S. Das, "Low Complexity Near Optimal Multiuser Detection Scheme for SDMA-OFDM System," in Proc. Int. Conf., Devices Commun. (ICDeCom), Mesra, India, Feb. 24-25, 2011, pp. 1-5.
  7. M. Jiang and L. Hanzo, "Genetically Enhanced TTCM Assisted MMSE Multi-user Detection for SDMA-OFDM," in Proc. Veh. Technol. Conf., Los Angeles, CA, USA, Sept. 26-29, 2004, pp. 1954-1958.
  8. W. Bocquet, K. Hayashi, and H. Sakai, "On the SIC Detection with Adaptive MMSE Equalization for MIMO-OFDM Transmissions," in Proc. IEEE VTS Asia Pacific Wireless Commun. Symp., Hsinchu, Taiwan, Aug. 2007, pp. 1-5.
  9. J.I. Abahneh, T.F. Aldalgamouni, and A.A. Alqudah, "Minimum Bit Error Rate Multiuser Detection of SDMA- OFDM System Using Differential Evolutionary Algorithm," in Proc. IEEE Int. Conf. Wireless Mobile Comput., Netw. Commun. (WiMob), Niagara Falls, Canada, Oct. 11-13, 2010, pp. 273-279.
  10. S. Shibina and M. Mathurakani, "Nature Inspired Solution for Optimum Multiuser Detection in SDMA OFDM Systems," Proc. Global Conf. Commun. Technol. (GCCT), Thuckalay, India, Apr. 23-24, 2015, pp. 863-868.
  11. U. Yesilyurt and O. Ertug, "Hybrid ML-MMSE Adaptive Multiuser Detection Based on Joint Channel Estimation in SDMA-OFDM Systems," in Proc. Int. Conf. Softw. Telecommun. Comput. Netw., Split, Croatia, Sept. 21-23, 2017, pp. 1-5.
  12. W.S. Choi, H.S. Chang, P.S. Kim, and J.G. Kim, "Joint ML & MMSE-SIC Detection for Multi Cell Network Environment," in Proc. Signal Process. Commun. Syst. (ICSPCS), Gold Coast, Australia, Dec. 15-17, 2014, pp. 1-5.
  13. M. Alansi, I. Elshafiye, and A. Al-Sanie, "Genetic Algorithm Implementation of Multi-user Detection in SDMA-OFDM Systems," in Proc. Signal Process. Inform. Technol. (ISSPIT), Bilbao, Spain, Dec. 14-17, 2011, pp. 316-320.
  14. C.H. Tsai, W.H. Fang, and J.T. Chen, "Hybrid MMSE and SIC for Multiuser Detection," in Proc. IEEE Veh. Technol. Conf., Rhodes, Greece, May 6-9, 2001, pp. 1779-1783.
  15. M.A.M. Moqbel, W. Wangdong, and A.Z. Ali, "MIMO Channel Estimation Using the LS and MMSE Algorithm," IOSR J. Electron. Commun. Eng., vol. 12, no. 1, Jan. 2017, pp. 13-22.
  16. S.M. Patil and A.N. Jadhav, "Channel Estimation Using LS and MMSE Estimators," Int. J. Recent Innovation Trends Comput. Commun., vol. 2, Mar. 2014, pp. 566- 570.
  17. X. Sun and R. Qiao, "Joint ML and MMSE Estimation Based Signal Detection for MIMO-OFDM Radio Over Fiber System," in Proc. IEEE Int. Conf. Embedded Soft. Syst. High Performance Comput. Commun., Liverpool, UK, June 25-27, 2012, pp. 187-192.
  18. L. Dai, X. Sun, and H. Chen, "A New Selective Signal Detection Based on Iterative Joint Channel Estimation in MIMO-OFDM Systems," in Proc. IEEE Int. Conf. Wirel. Commun., Netw. Inform., Sec. (WCNIS), Beijing, China, June 25-27, 2010, pp. 80-84.
  19. D. Kong, J. Zeng, X. Su, L. Rong, and X. Xu, "Multiuser Detection Algorithm for PDMA Uplink System Based on SIC and MMSE," in Proc. IEEE/CIC Int. Conf. Commun. China, Chengdu, China, July 27-29, 2016, pp. 1-5.