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Performance Analysis of Multistage Interference Cancellation in THUWB Systems Using Adaptive Differential Evolution Algorithm with Novel Mutation and Crossover Strategies

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Abstract

We study the application of differential evolution optimization algorithm to the problem of multiuser detection (MUD) and the suppression of multiple-access interference (MAI) in time-hopping UWB (TH-UWB) system is carried out considering the performance-complexity trade-off. The importance of MUD for achieving high data or low bit error rates in these systems has already been established in several studies. However, the optimum MUD can be characterized as a nondeterministic polynomial-time hard combinatorial optimization problem such that the computational complexity increases exponentially with number of user. In this paper, we proposed modified differential evolution (MDE) optimization algorithm with novel mutation and crossover strategy based MUD is investigated by simulations, when communicating over Saleh–Valenzuela (S–V) channel model. The RAKE detector is used as the first stage to initialize the MDE-based MUD. Then, the MDE algorithm is applied to detect the received data bit by optimizing an objective function incorporating the system of the RAKE detector. The performance evaluation with extensive simulations show that our proposed MDE based MUD can go to convergence rapidly under TH-UWB channel model, the bit error ratio performance is better than of the traditional MUD.

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References

  1. Reed, J. H. (2005). An introduction to ultrawideband communication systems. Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  2. Win, M. Z., & Scholtz, R. A. (2000). Ultra-wide bandwidth time-hopping spread-spectrum impulse radio for wireless multiple-acess communications. IEEE Transactions on Communications, 48(4), 679–689.

    Article  Google Scholar 

  3. Foerster, J., et al. (2003, February). Channel modeling sub-committee report final. IEEE 802. 15 working group for wireless personal area networks (WPANs), IEEE P802.15-02/490r1-SG3a

  4. Shao, Hua, & Beaulieu, N. C. (2011). Direct sequence and time-hopping sequence designs for narrowband interference mitigation in impulse radio UWB Systems. IEEE Transactions on Communications, 59, 1957–1965.

    Article  Google Scholar 

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

    MATH  Google Scholar 

  6. Scholtz, R. A. (1993). Multiple access with time-hopping impulse modulation. In Proceedings of the IEEE military communications conference, Boston, MA, Vol. 2, pp. 447–450

  7. Cassioli, D., Win, M. Z., & Vatalaro, F. (2007). Low complexity rake receivers in ultra wideband channels. IEEE Transactions on Wireless Communications, 6, 1265–1275.

    Article  Google Scholar 

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

    Article  Google Scholar 

  9. Yoon, Y. C., & Kohno, R. (2002, April). Optimum multi-user detection in ultrawideband (UWB) multiple-access communication systems. In Proceedings of the IEEE international conference on communications, New York, pp. 812–816

  10. Win, M. Z., & Scholtz, R. A. (2000). Ultra-wide bandwidth time-hopping spread-spectrum impulse radio for wireless multiple-access communications. IEEE Transactions on communications, 48(4), 679–691.

    Article  Google Scholar 

  11. Hu, B., & Beaulieu, N. C. (2004). Accurate evaluation of multiple-access performance in TH-PPM and TH-BPSK UWB systems. IEEE Transactions on communications, 52(10), 1758–1766.

    Article  Google Scholar 

  12. Dhibi, Y., & Kaiser, T. (2006). On the impulsiveness of multiuser interferences in TH-PPM UWB systems. IEEE Transactions on Signal Processing, 54(7), 2853–2857.

    Article  Google Scholar 

  13. Ahmed, Q. Z., Yang, Lie-Liang, & Chen, Sheng. (2011). Reduced-rank adaptive least bit-error-rate detection in hybrid direct-sequence time-hopping ultrawide bandwidth systems. IEEE Transactions on Vehicular Technology, 60, 849–857.

    Article  Google Scholar 

  14. Li, Qinghua, & 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.

    Article  Google Scholar 

  15. Li, Sheng, & de Lamare, R. C. (2011). Blind reduced-rank adaptive receivers for DS-UWB systems based on joint iterative optimization and the constrained constant modulus criterion. IEEE Transactions on Vehicular Technology, 60(6), 2505–2518.

    Article  Google Scholar 

  16. Miguez, J., & Castedo, L. (1998). A linearly constrained constant modulus approach to blind adaptive multiuser interference suppression. IEEE Communications Letters, 2, 217–220.

    Article  Google Scholar 

  17. Bharadwaj, V., & Buehrer, R. M. (2005). An interference suppression scheme for UWB signals using multiple receive antennas. IEEE Communications Letters, 9, 529–531.

    Article  Google Scholar 

  18. De Jong, K. (2006). Evolutionary computation: A unified approach. Cambridge, MA: MIT Press.

    Google Scholar 

  19. Holland, J. H. (1975). Adaptation in natural and artificial systems. Ann Arbor: University Michigan Press.

    Google Scholar 

  20. Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In Proceedings of the IEEE international conference on neural networks, Vol. 4, 1995, pp. 1942–1948

  21. Dorigo, M., Caro, G. D., & Gambardella, L. M. (1999). Ant algorithms for discrete optimization. Artificial Life, 5(2), 137–172.

    Article  Google Scholar 

  22. Yao, Y.-C., Cheng, C.-H., Wen, G.-J., & Wen, J.-H. (2011). Multiuser detection using simulated annealing Hopfield neural network for DS-UWB systems. In 2011 International conference on machine learning and cybernetics (ICMLC), Vol. 2, pp. 763–768

  23. Nam, P., Malinowski, A., & Bartczak, T. (2011). Comparative study of derivative free optimization algorithms. IEEE Transactions on Industrial Informatics, 7(4), 592–600.

    Article  Google Scholar 

  24. Storn, R., & Price, K. V. (1995). Differential evolution—A simple and efficient adaptive scheme for global optimization over continuous spaces. Technical report TR-95-012, ICSI, http://http.icsi.berkeley.edu/~storn/litera.html

  25. Price, K. V., Storn, R., & Lampinen, J. (2005). Differential evolution—A practical approach to global optimization. Berlin: Springer.

    MATH  Google Scholar 

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

    Article  Google Scholar 

  27. Fishler, E., & Poor, H. V. (2004). Low-complexity multiuser detectors for time-hopping impulse-radio systems. IEEE Transactions on Signal Processing, 52(9), 2561–2571.

    Article  MathSciNet  Google Scholar 

  28. Eiben, A. E., Hinterding, R., & Michalewicz, Z. (1999). Parameter control in evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 3(2), 124–141.

    Article  Google Scholar 

  29. Islam, Sk Minhazul, Swagatam, Das, Ghosh, S., Roy, S., & Suganthan, P. N. (2012). An adaptive differential evolution algorithm with novel mutation and crossover strategies for global numerical optimization. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42, 482–500.

    Article  Google Scholar 

  30. Epitropakis, Michael G., Tasoulis, Dimitris K., Pavlidis, Nicos G., Plagianakos, Vassilis P., & Vrahatis, Michael N. (2011). Enhancing differential evolution utilizing proximity-based mutation operators. IEEE Transactions on Evolutionary Computation, 15(1), 99–119.

    Article  Google Scholar 

  31. Das, Swagatam, & Suganthan, P. N. (2011). Differential evolution: A survey of the state-of-the-art. IEEE Transactions on Evolutionary Computation, 15(1), 4–31.

    Article  Google Scholar 

  32. Qin, A. K., Huang, V. L., & Suganthan, P. N. (2009). Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Transactions on Evolutionary Computation, 13(2), 398–417.

    Article  Google Scholar 

  33. Koziel, S., & Michalewicz, Z. (1999). Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization. Evolutionary Computation, 7(1), 19–44.

    Article  Google Scholar 

  34. Feoktistov, V. (2006). Differential evolution in search of solutions. Berlin: Springer.

    MATH  Google Scholar 

  35. Kouassi, K., Clavier, L., Doumbia, I., & Rolland, P. (2013). Optimal PWR codes for TH-PPM UWB multiple-access interference mitigation. IEEE Communications Letters, 17(1), 103–106.

    Article  Google Scholar 

  36. Niranjayan, S., & Beaulieu, Norman C. (2013). Novel adaptive nonlinear receivers for UWB multiple access communications. IEEE Transactions on Wireless Communications, 12(5), 2014–2023.

    Article  Google Scholar 

  37. Nader-Esfahani, S., Rezaii, M., & Ghasemi, A. (2012). On optimal front-end filter for single-user detection in IR-UWB systems. IEEE Transactions onCommunications, 60, 37–41.

    Article  Google Scholar 

  38. Thotahewa, K. M. S., Redoute, J.-M., & Yuce, M. R. (2013). SAR, SA, and temperature variation in the human head caused by IR-UWB implants operating at 4 GHz. IEEE Transactions on Microwave Theory and Techniques, 61(5, Part: 2), 2161–2169.

    Article  Google Scholar 

  39. Xiong, Hailiang, Zhang, Wensheng, He, Bo, & Yuan, Dongfeng. (2013). Front-end narrowband interference mitigation for DS-UWB receiver. IEEE Transactions on Wireless Communications, 12(9), 4328–4337.

    Article  Google Scholar 

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  1. Information and Network Communication, Chien-Kuo Technology University, No. 1 Chien Shou Rd., Changhua, Taiwan

    Ho-Lung Hung

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  1. Ho-Lung Hung
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Hung, HL. Performance Analysis of Multistage Interference Cancellation in THUWB Systems Using Adaptive Differential Evolution Algorithm with Novel Mutation and Crossover Strategies. Wireless Pers Commun 82, 1179–1199 (2015). https://doi.org/10.1007/s11277-015-2274-9

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  • DOI: https://doi.org/10.1007/s11277-015-2274-9

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