Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Stochastic resonator to detect bipolar binary pulse amplitude modulated signals; analysis, parameter-induced SR designs and sine-induced SR

© The Institution of Engineering and Technology
Received 20/04/2015, Accepted 27/05/2016, Revised 29/04/2016, Published 07/06/2016

A stochastic resonator has been considered as an alternative signal processing tool because of its noise-induced performance enhancement ability. Here, the resonator parameters, steady states and transition time of the system are redefined for bipolar binary pulse amplitude modulated (BPAM) signals such that the region in which the resonator benefits from noise can be identified. Simple parameter-induced SR (PSR) designs are then built, based on this analysis in order to configure the resonator in the optimum region. Furthermore, sine-induced SR based on using a periodic signal instead of noise is introduced to enhance the system performance and compared with noise-enhanced SR (NSR). It is shown that sine-induced SR provides a performance enhancement as it needs less power and does not require an adjustment relevant to the background noise. The results indicate that a resonator improves the receiver performance by eliminating noise if its parameters and BPAM characteristics are set accurately as given in the PSR designs, otherwise the resonator can benefit from either a noise as in NSR, or a sine wave as proposed.

Inspec keywords: interference suppression; pulse amplitude modulation; signal detection

Other keywords: receiver performance; stochastic resonator; noise-induced performance enhancement; bipolar binary pulse amplitude modulated signal; periodic signal; BPAM signal; signal detection; parameter-induced SR designs; background noise; noise elimination; resonator parameters; sine-induced SR

Subjects: Signal detection; Modulation and coding methods; Signal processing theory; Electromagnetic compatibility and interference

References

    1. 1)
      • 5. Benzi, R., Parisi, G., Sutera, A., et al: ‘Stochastic resonance in climatic change’, Tellus, 1982, 34, (1), pp. 10–16.
    2. 2)
      • 2. Liu, Z., Lai, Y.-C., Nachman, A.: ‘Enhancement of noisy signals by stochastic resonance’, Phys. Lett. A, 2002, 297, (12), pp. 75–80.
    3. 3)
      • 6. Gammaitoni, L., H¨anggi, P., Jung, P., et al: ‘Stochastic resonance: a remarkable idea that changed our perception of noise’, Eur. Phys. J. B, 2009, 69, (1), pp. 1–3.
    4. 4)
      • 15. Guo, Y., Tan, J.: ‘Suprathreshold stochastic resonance in multilevel threshold system driven by multiplicative and additive noises’, Commun. Nonlinear Sci. Numer. Simul., 2013, 18, (10), pp. 2852–2858.
    5. 5)
      • 12. Barbini, L., Cole, M.O.T., Hillis, A.J., et al: ‘Weak signal detection based on two dimensional stochastic resonance’. 23rd European Signal Processing Conf. (EUSIPCO), 2015, August 2015, pp. 2147–2151.
    6. 6)
      • 10. Chen, H., Varshney, P.: ‘Theory of the stochastic resonance effect in signal detection part ii: variable detectors’, IEEE Trans. Signal Process., 2008, 56, (10), pp. 5031–5041.
    7. 7)
      • 18. Liu, J., Li, Z., Guan, L., et al: ‘A novel parameter-tuned stochastic resonator for binary pam signal processing at low snr’, IEEE Commun. Lett., 2014, 18, (3), pp. 427–430.
    8. 8)
      • 19. Liu, J., Li, Z.: ‘Lowering the signal-to-noise ratio wall for energy detection using parameter induced stochastic resonator’, Commun. IET, 2015, 9, (1), pp. 101–107.
    9. 9)
      • 1. Kocaoglu, M., Gulbahar, B., Akan, O.: ‘Stochastic resonance in graphene bilayer optical nanoreceivers’, IEEE Trans. Nanotechnol., 2014, 13, (6), pp. 1107–1117.
    10. 10)
      • 4. Benzi, R., Sutera, A., Vulpiani, A.: ‘The mechanism of stochastic resonance’, J. Phys. A, Math. General, 1981, 14, (11), p. L453.
    11. 11)
      • 7. Moss, F., Ward, L.M., Sannita, W.G.: ‘Stochastic resonance and sensory information processing: a tutorial and review of application’, Clin. Neurophysiol., 2004, 115, (2), pp. 267–281.
    12. 12)
      • 20. Mitaim, S., Kosko, B.: ‘Adaptive stochastic resonance’, Proc. IEEE, 1998, 86, (11), pp. 2152–2183.
    13. 13)
      • 24. Ai-Jie, L., Lian-Cun, Z., Lian-Xi, M., et al: ‘Analytical solutions of a model for Brownian motion in the double well potential’, Commun. Theor. Phys., 2015, 63, (1), p. 51.
    14. 14)
      • 9. Chen, H., Varshney, P., Kay, S., et al: ‘Theory of the stochastic resonance effect in signal detection: Part i – fixed detectors’, IEEE Trans. Signal Process., 2007, 55, (7), pp. 3172–3184.
    15. 15)
      • 3. Albert, T., Bulsara, A., Schmera, G., et al: ‘An evaluation of the stochastic resonance phenomenon as a potential tool for signal processing’. Conf. Record of The Twenty-Seventh Asilomar Conf. on Signals, Systems and Computers, November 1993, vol. 1, pp. 583–587.
    16. 16)
      • 23. Misono, M., Kohmoto, T., Fukuda, Y., et al: ‘Stochastic resonance in an optical bistable system driven by colored noise’, Opt. Commun., 1998, pp. 152, (4–6), pp. 255–258.
    17. 17)
      • 11. McNamara, B., Wiesenfeld, K.: ‘Theory of stochastic resonance’, Phys. Rev. A, 1989, 39, (9), pp. 4854–4869.
    18. 18)
      • 21. Gammaitoni, L., H¨anggi, P., Jung, P., et al: ‘Stochastic resonance’, Rev. Modern Phys., 1998, 70, (1), pp. 223–287.
    19. 19)
      • 14. Zhang, X., Xu, W.: ‘Stochastic resonance in an asymmetric bistable system with coloured noises and periodic rectangular signal’, Phys. A, Stat. Mech. Appl., 2007, 385, (1), pp. 95–104.
    20. 20)
      • 13. Dubkov, A., Spagnolo, B., Valenti, D.: ‘New analytical approach to analyze the nonlinear regime of stochastic resonance’. Int. Conf. on Noise and Fluctuations (ICNF), 2015, June 2015, pp. 1–4.
    21. 21)
      • 8. McDonnell, M.D., Abbott, D.: ‘What is stochastic resonance? definitions, misconceptions, debates, and its relevance to biology’, PLoS Comput. Biol., 2009, 5, (5), p. e1000348.
    22. 22)
      • 22. Moss, F.: ‘Stochastic resonance: a signal + noise in a two state system’. Proc. of the 45th Annual Symp. on Frequency Control, May 1991, pp. 649–658.
    23. 23)
      • 17. Zozor, S., Amblard, P.-O.: ‘Stochastic resonance in locally optimal detectors’, IEEE Trans. Signal Process., 2003, 51, (12), pp. 3177–3181.
    24. 24)
      • 16. Shao, R.H., Chen, Y.: ‘Stochastic resonance in time-delayed bistable systems driven by weak periodic signal’, Phys. A, Stat. Mech. Appl., 2009, 388, (6), pp. 977–983.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-spr.2015.0152
Loading

Related content

content/journals/10.1049/iet-spr.2015.0152
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address