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Multi-objective optimization for UWB antenna array by APSO algorithm

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Abstract

In this paper, a uniform circular antenna array (UCAA) combining genetic algorithm (GA) or asynchronous particle swarm (APSO) for finding out global maximum of multi-objective function in indoor ultra-wideband (UWB) communication system is proposed. The algorithm is used to synthesize the radiation pattern of the directional UCAA to reduce the bit error rate (BER), to increase received energy and channel capacity in indoor UWB communication system. Using the impulse response of multipath channel, the BER of the synthesized antenna pattern on binary antipodal-pulse amplitude modulation system can be calculated. Based on topography of the antenna and the shooting and bouncing ray/image techniques, the synthesized problem can be reformulated into a multi-objective optimization problem which would be solved by the GA and APSO. Numerical results show that the fitness value and convergence speed by APSO is better than those by GA. The results also show that for multi-objective problem APSO compared to GA can reduce the BER substantially. Moreover, APSO can get better results for both line-of-sight and non line-of-sight cases.

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References

  1. Federal Communications Commission (2002). Revision of Part 15 of the commission’s rules regarding ultra-wideband transmission system, first report and order, FCC, ET Docket, pp. 1–118.

  2. Colak, S., Wong, T. F., & Serbest, A. H. (2007). UWB dipole array with equally spaced elements of different lengths. In IEEE international conference on ultra-wideband, pp. 789–793.

  3. Malik, W. Q., Edwards, D. J., & Stevens, C. J. (2006). Angular-spectral antenna effects in ultra-wideband communications links. In IEE proceedings communications, 153(1).

  4. Funk, E. E., & Lee, C. H. (1996). Free-space power combining and beam steering of ultra-wideband radiation using an array of laser-triggered antennas. IEEE Transactions on Microwave Theory and Techniques, 44, 2039–2044.

    Article  Google Scholar 

  5. Yazdandoost, K. Y., & Kohno, R. (2004). Free-space power combining and beam steering of ultra-wideband radiation using an array of laser-triggered antennas. IEEE Communication Magazine, 42(6), 29–32.

    Article  Google Scholar 

  6. Ghavami, M. (2002). Wideband smart antenna theory using rectangular array structures. IEEE Transactions on Signal Processing, 50(9), 2143–2151.

    Article  Google Scholar 

  7. Tarokh, V., Seshadri, N., & Calderbank, A. R. (1998). Space-time codes for highdatarate wireless communications: Performance criterion and code construction. IEEE Transactions on Information Theory, 44, 744–745.

    Article  Google Scholar 

  8. Chen C.-H., & Chiu, C. C. (2000). Novel optimum radiation pattern by genetic algorithms in indoor wireless local loop. In IST mobile summit 2000, Galway, Ireland, pp. 391–399.

  9. Peng, M., & Wang, W. (2005). Comparison of capacity between adaptive tracking and switched beam smart antenna techniques in TDD-CDMA systems. Microwave, Antenna, Propagation and EMC Technologies for, Wireless Communications, 2005(1), 135–139.

    Google Scholar 

  10. Choi, J. (2015). Iterative methods for physical-layer multicast beamforming. IEEE Transactions on Wireless Communications, 14, 5185–5196.

    Article  Google Scholar 

  11. He, S., Huang, Y., Yang, L., Ottersten, B., & Hong, W. (2015). Energy efficient coordinated beamforming for multicell system: Duality-based algorithm design and massive MIMO transition. IEEE Transactions on Communications, 63, 4920–4935.

    Article  Google Scholar 

  12. Sakamoto, K., Arai, M., Hiraga, K., Seki, T., Tsubaki, T., Toshinaga, H., et al. (2015). A novel ZF-based fast beamforming method for short-range MIMO transmission. IEEE Transactions on Wireless Communications, 4, 557–560.

    Article  Google Scholar 

  13. Liu, G., Richard Yu, F., Ji, H., & Leung, V. C. M. (2015). Energy-efficient resource allocation in cellular networks with shared full-duplex relaying. IEEE Transactions on Vehicular Technology, 64, 3711–3724.

    Article  Google Scholar 

  14. Salameh, H. B., & Hailat, T. (2015). Iterative beamforming algorithm for improved throughput in multi-cell multi-antenna wireless systems. IET Communications, 9(13), 1619–1626.

    Article  Google Scholar 

  15. Ma, J., Li, P., Lin, X., Zhu, W., & Yuan X. (2005) Game theory method for multi-objective optimizing operation in microgrid. IEEE 12th international conference on networking, sensing and control (ICNSC), pp. 421–425.

  16. Kolbin, V. V., & Perestoronin, D. S. (2005). Several problems of the stability of multi-objective optimization. In International conference in memory of V.I. Zubov (SCP), pp. 16–19.

  17. Maheta, H. H., & Dabhi, V. K. (2015). Classification of imbalanced data sets using multi objective genetic programming. International conference on computer communication and informatics, (ICCCI), pp. 1–6.

  18. Chen, C.-H., Chiu, C.-C., Ching-Yun, W., & Shu-Han L. (2013). A multi-objective optimization for UWB antenna array in indoor environment. In International symposium intelligent signal processing and communications systems (ISPACS). pp. 565–568.

  19. Zhang H., & Zhang H. (2014). A new method for objective weights computing in multi-objective optimization. In IEEE 9th conference on industrial electronics and applications (ICIEA), pp. 2019–2022.

  20. David, K. (1989). Cheng, field and wave electromagnetics. Reading, MA: Addison-Wesley Publishing Company Press.

    Google Scholar 

  21. Gueguen, E., Thudor, F., & Chambelin, P. (2005). A low cost UWB printed dipole antenna with high performance. In IEEE international conference on ultra-wideband (ICU’05), pp. 88–92.

  22. Talom, F. T., Uguen, B., Rudant, L., Keignart, J., Pintos, J. F., & Chambelin, P. (2006). Evaluation and characterization of an UWB antenna in time and frequency domains. IEEE international conference on ultra-wideband (ICU’06), pp. 669–673.

  23. Gueguen, E., Thudor, F., & Chambelin, P. (2005). A low cost UWB printeddipole antenna with high performance. In IEEE international conference on ultra-wideband, pp. 89–92.

  24. Talom, F. T., Uguen, B., Rudant, L., Keignart, J., Pintos, J.-F., & Chambelin, P. (2006). Evaluation and characterization of an UWB antenna in time and frequency domains. In IEEE international conferenceonultra-wideband, pp. 669–673.

  25. Manteuffel, D. (2006). Radio link characterization using real antenna integration scenarios for UWB consumer electronic applications, ultra wideband systems, technologies and applications (pp. 123–130). Seminar: The Institution of Engineering and Technology.

  26. El-Hadidy, M., & Kaiser, T. (2006). Impact of ultra wide-band antennas on communications in a spatial cannel. In 1st international cognitive radio oriented wireless networks and communications, pp. 1–5.

  27. Chen, S. H., & Jeng, S. K. (1995). An SBR/image approach for indoor radio propagation in a corridor. In IEICE transactions on electronics, vol. E78-C, no.8, pp. 1058–1062.

  28. Chen, S. H., & Jeng, S. K. (1996). SBR image approach for radio wave propagation in tunnels with and without traffic. IEEE Transactions on Vehicular Technology, 45(3), 570–578.

    Article  Google Scholar 

  29. Liao, S. H., Ho, M. H., & Chiu, C. C. (2010). Bit error rate reduction for multiusers by smart UWB antenna array. In Progress In electromagnetic research C (PIER C), vol. 16, pp. 85–98.

  30. Clerc, M., & Kennedy, J. (2002). The particle swarm-explosion, stability andconvergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation, 6(1), 58–73.

    Article  Google Scholar 

  31. Carlisle, A., & Dozier, G. (2001). An off-the-shelf PSO. In Indianapolis: Proceedings of the workshop on particle swarm optimization.

  32. Goldberg, D. E. (1989). Genetic algorithm in search, optimization and machine learning. Reading, MA: Addison Wesley.

  33. Johnson, J. M., & Rahmat-Samii, Y. (1997). Genetic algorithms in engineering electromagnetics. IEEE Antennas and Propagation Magazine, 39(4), 7–21.

    Article  Google Scholar 

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Correspondence to Chien-Ching Chiu.

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Chien, W., Chiu, CC., Cheng, YT. et al. Multi-objective optimization for UWB antenna array by APSO algorithm. Telecommun Syst 64, 649–660 (2017). https://doi.org/10.1007/s11235-016-0197-8

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