Abstract
In wireless sensor network communication system, the interference caused by random spread spectrum leads to poor communication quality and high bit error rate of communication network array signals. The invention provides a wireless sensor network communication network array signal synchronization transmission algorithm based on Gaussian fuzzy algorithm. Wireless sensor network communication channel model is established within the building and code interference suppression algorithm, using a Gaussian blur algorithm for array signal synchronization control, communication network and the communication network of array signal multipath structure harmonic balance equation, the structure and design of the matched filter detector, implements the communication network optimization of array signal synchronous transmission. The simulation results show that the algorithm can realize the synchronous transmission of the communication network array signals in the wireless sensor network communication, greatly improve the output SNR, greatly reduce the bit error rate of the wireless sensor network communication system, and improve the communication quality and performance.
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Wu, J. G., Shao, T., & Liu, Z. Y. (2017). RGB-D saliency detection based on integration feature of color and depth saliency map. Journal of Electronics and Information Technology, 39(9), 2148–2154.
Carlson, N. A., & Porter, J. R. (2017). On the cardinality of Hausdorff spaces and H-closed spaces. Topology and its Applications, 160(1), 137–142.
Zhang, T., Mu, D. J., Ren, S., et al. (2014). Information hiding scheme for 3D models based on skeleton and inscribed sphere analysis. Journal of Xidian University, 41(2), 185–190.
Ang, L. F., Cheng, X. I., Qin, P. L., et al. (2018). Non-rigid multi-modal medical image registration based on multi-channel sparse coding. Journal of Computer Applications, 38(4), 1127–1133.
Lu, Z. T., Zhang, J., Feng, Q. J., et al. (2015). Medical image registration based on local variance and residual complexity. Chinese Journal of Computers, 38(12), 2400–2411.
Ghaffari, A., & Fatemizadeh, E. (2014). Sparse-induced similarity measure: Mono-modal image registration via sparse-induced similarity measure. IET Image Processing, 8(12), 728–741.
Litjens, G., Kooi, T., Bejnordi, B. E., et al. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis, 42(9), 60–88.
Ferrara, P., & Bianchi, T. (2012). Image forgery localization via fine-grained analysis of CFA artifacts. IEEE Transactions on Information Forensics and Security, 7(5), 1566–1577.
Tengfei, L., & Weili, J. (2014). Automatic line segment registration using Gaussian mixture model and expectation-maximization algorithm. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(5), 1688–1699.
Siwei, L., Xunyu, P., & Xing, Z. (2014). Exposing region splicing forgeries with blind local noise estimation. International Journal of Computer Vision, 110(2), 202–221.
Cheung M.H., Southwell R., Hou F., et al. (2015) Distributed time-sensitive task selection in mobile crowdsensing. In: Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing. New York: ACM, 157–166.
Rui, L. L., Zhang, P., Huang, H. Q., et al. (2016). Reputation-based incentive mechanisms in crowdsourcing. Journal of Electronics and Information Technology, 38(7), 1808–1815.
Zhang, Y., Jiang, C., Song, L., et al. (2017). Incentive mechanism for mobile crowdsourcing using an optimized tournament model. IEEE Journal on Selected Areas in Communications, 35(4), 880–892.
Koivumaki, J., & Mattila, J. (2017). Stability-guaranteed impedance control of hydraulic robotic manipulators. IEEE/ASME Transactions on Mechatronics, 22(2), 601–612.
Koivumaki, J., & Mattila, J. (2015). Stability-guaranteed force-sensorless contact force/motion control of heavy-duty hydraulic manipulators. IEEE Transactions on Robotics, 31(4), 918–935.
Gao, J. (2019). Simulation of dynamic user network connection anti-interference and security authentication method. Computer Simulation, 36(5), 230–233.
Wanderoild, Y., Asfour, A., Lefranc, P., et al. (2017). Giant magneto-impedance sensor for gate driver-insulated signal transmission functions. IEEE Transactions on Power Electronics, 32(4), 2493–2497.
Schrenk, B. (2019). Synchronized wavelength-swept signal transmission and its ability to evade optical reflection crosstalk. Optics Letters, 44(11), 2771–2776.
Han, Y. S., Zhang, W. F., Zhang, J. J., et al. (2017). Two microwave vector signal transmission on a single optical carrier based on PM-IM conversion using an on-chip optical Hilbert transformer. Journal of Lightwave Technology, 12(9), 1–6.
Sultana, J., Islam, M. S., Atai, J., et al. (2017). Novel near zero dispersion flattened, low loss porous core waveguide design for terahertz signal transmission. Optical Engineering, 56(7), 114–118.
Feng, J., Li, Z. X., Jiang, M. F., et al. (2017). Signal gain mechanism for a hollow transmission pressure bar with an end cap. Experimental Mechanics, 58(6), 1–11.
Remon, D., Cañizares, C. A., & Rodriguez, P. (2017). Impact of 100-MW-scale PV plants with synchronous power controllers on power system stability in northern Chile. Iet Generation Transmission and Distribution, 11(11), 2958–2964.
Hyounguk, K., Kinam, J., Seon, J. Y., et al. (2018). Long-distance transmission of broadband near infrared light guided by semi-disordered 2D array of metal nanoparticles. Nanoscale, 10(45), 17–24.
Sang, M. J., Kyoung, H. M., Soo, M. K., et al. (2017). Optical signal suppression by a cascaded SOA/RSOA for wavelength reusing reflective PON upstream transmission. Optics Express, 25(19), 22–28.
Ugalde-Loo, C. E., Acha, E., & Licéaga-Castro, E. (2018). Analysis of the damping characteristics of two power electronics-based devices using individual channel analysis and design. Applied Mathematical Modelling, 59, 19–23.
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Zhong, J. Communication network array signal synchronous transmission method based on Gaussian fuzzy algorithm. Wireless Netw 28, 2289–2298 (2022). https://doi.org/10.1007/s11276-021-02705-z
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DOI: https://doi.org/10.1007/s11276-021-02705-z