Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Performance of multiuser detectors based on EM-like method for ultra-wideband communications systems in multipath fading channel

  • 130 Accesses

  • 2 Citations


An adaptive multiuser detector (MUD) is proposed for direct-sequence ultra-wideband (DS-UWB) multiple access communication systems to suppress both multiple access interference (MAI) and inter-symbol interference (ISI). In this contribution, considering the MUD from a combination viewpoint, we proposed a MUD based on electromagnetism-like (EM) method, which applied the concept of EM search to Hopfield neural network (EMHNN) for solving optimization problems. We analyze the performance of the EMHNN MUD in multipath fading channel, and compare it with the optimum detector and several suboptimum schemes such as conventional, decorrelator detector (DD), minimum-mean-squared error (MMSE) and HNN MUD. Simulation results will demonstrate that the proposed EMHNN MUD, which alleviates the detrimental effects of the MAI problem, can significantly improve the system performance.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11


  1. 1.

    Win, M. Z., & Scholtz, R. A. (1998). Impulse radio: how it works. IEEE Communications Letters, 2(2), 36–38.

  2. 2.

    Yang, L., & Giannakis, G. B. (2004). Ultra-wideband communications an idea whose time has come. IEEE Signal Processing Magazine, 21(6), 26–54.

  3. 3.

    Yang, L., & Giannakis, G. B. (2005). A general model and SINR analysis of low duty-cycle UWB access through multipath with narrowband interference and rake reception. IEEE Transactions on Wireless Communications, 4(4), 1818–1833.

  4. 4.

    Guvenc, I., & Arslan, H. (2007). A review on multiple access interference cancellation and avoidance for IR-UWB. Signal Processing, 87, 623–653.

  5. 5.

    Li, Q., & Rusch, L. A. (2002). Multiuser detection for DS-CDMA UWB in the home environment. IEEE Journal on Selected Areas in Communications, 20(9), 1701–1711.

  6. 6.

    Boubaker, N., & Ben Letaief, K. (2004). Combined multiuser successive interference cancellation and partial rake reception for ultra-wideband wireless communication. In IEEE vehicular technology conference (pp. 1209–1212).

  7. 7.

    Foerster, J. R. (2002). The performance of a direct-sequence spread ultra wide-band system in the presence of multipath, narrowband interference, and multiuser interference. In IEEE conf. ultra wideband syst. technologies (pp. 87–91).

  8. 8.

    Yoon, Y. C., & Kohno, R. (2002). Optimum multiuser detection in ultra wide-band multiple-access communication systems. In Proc. IEEE international conf. on commun. (pp. 812–816).

  9. 9.

    Zhang, Y., Lu, W.-S., & Gulliver, T. A. (2005). Recursive multiuser detection for DS-UWB systems. In IEEE Pacific Rim conference on communications, computers and Signal processing (PACRIM 2005) (pp. 534–537).

  10. 10.

    Lin, L., & Wang, A. (2008). New hybrid multiuser receiver for DS-UWB system. In IEEE wireless communications, networking and mobile computing (pp. 1–5).

  11. 11.

    Tan, T.-H., Huang, Y.-F., Lin, C.-W., & Fu, R.-H. (2006). Performance improvement of multiuser detection using a genetic algorithm in DS-CDMA UWB systems over an extreme NLOS multipath channel. In Proc. of IEEE SMC 2006 (pp. 1945–1950).

  12. 12.

    Choi, J. D., & Stark, W. E. (2002). Performance of ultra-wideband communications with suboptimal receivers in multipath channel. IEEE Journal on Selected Areas in Communications, 20, 1754–1766.

  13. 13.

    Fogle, D. B. (2002). Evolutionary computation: toward a new philosophy of machine intelligence (2nd ed.). Piscataway: IEEE Press.

  14. 14.

    Kennedy, J., & Eberhart, R. C. (1995). Particle swarm optimization. In Proc. IEEE international conf. on neural networks, Perth, Australia (pp. 1942–1947).

  15. 15.

    Hung, H.-L., & Wen, J.-H. (2010). An adaptive multistage multiuser detector for MC-CDMA communication systems using evolutionary computation technique. Wireless Personal Communications, 53(4), 613–633.

  16. 16.

    Hung, H.-L., Lee, S.-H., Huang, Y.-F., & Wen, J.-H. (2009). Performance analysis of PSO-based parallel interference canceller for MC-CDMA communication systems. European Transactions on Telecommunications, 20, 287–297.

  17. 17.

    Soo, K. K., Siu, Y. M., Chan, W. S., Yang, L., & Chen, R. S. (2007). Particle swarm optimization-based multiuser detector for CDMA communication. IEEE Transactions on Vehicular Technology, 56, 3006–3013.

  18. 18.

    Yoon, S. H., & Rao, S. S. (2000). Annealed neural network based multiuser detector in code division multiple access communications. IEE Proceedings. Communications, 147, 57–62.

  19. 19.

    Fatih, A. (2003). A new algorithm for optimum multiuser detection in synchronous CDMA systems. AEÜ. International Journal of Electronics and Communications, 57(4), 263–269.

  20. 20.

    Paris, B.-P., Aazhang, B., & Orsak, G. (1992). Neural networks for multiuser detection in CDMA communication. IEEE Transactions on Communications, 40, 1212–1222.

  21. 21.

    Kechriotis, G. I., & Manolakos, E. S. (1996). Hopfield neural network implementation of the optimal CDMA multiuser detector. IEEE Transactions on Neural Networks, 7(1), 131–141.

  22. 22.

    Soujeri, E., & Bilgekul, H. (2002). Hopfield multiuser detection of asynchronous MC-CDMA signals in multipath fading channels. IEEE Communications Letters, 6(4), 147–149.

  23. 23.

    Birbil, S. İ., Fang, S.-C. (2003). An electromagnetism-like mechanism for global optimization. Journal of Global Optimization, 25(3), 263–282.

  24. 24.

    Birbil, S. İ., Fang, S.-C., & Sheu, R.-L. (2004). On the convergence of a population-based global optimization algorithm. Journal of Global Optimization, 30(2), 301–318.

  25. 25.

    Chang, P.-C., Chen, S.-H., & Fan, C.-Y. (2009). A hybrid electromagnetism-like algorithm for single machine scheduling problem. Expert Systems with Applications, 36, 1259–1267.

  26. 26.

    Saleh, A. A., & Valenzuela, R. A. (1987). A statically model for indoor multipath propagation. IEEE Journal on Selected Areas in Communications, 5(2), 128–137.

  27. 27.

    Verdú, S. (1998). Multiuser detection. Cambridge: Cambridge Univ. Press.

  28. 28.

    Verdú, S. (1986). Minimum probability of error for asynchronous Gaussian multiple-access channels. IEEE Transactions on Information Theory, 32(1), 85–96.

  29. 29.

    Proakis, J. G. (1995). Digital communications (3rd ed.). New York: Mc-Graw Hill.

  30. 30.

    Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences of the United States of America, 79, 2554–2558.

Download references

Author information

Correspondence to Yung-Fa Huang.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Hung, H., Huang, Y. Performance of multiuser detectors based on EM-like method for ultra-wideband communications systems in multipath fading channel. Telecommun Syst 53, 213–226 (2013). https://doi.org/10.1007/s11235-013-9694-1

Download citation


  • Ultra-wideband
  • Electromagnetism-like method
  • Hopfield neural network
  • Multiuser detection