Abstract
To improve the transmission performance of communication networks and reduce the bit error rate, it is necessary to design the transmission channel equalization in communication networks. A link equalization algorithm based on matched filter autocorrelation detection is proposed for wireless sensor networks. According to the characteristics of inter-symbol interference (ISI) of multipath components in wireless sensor network (WSN), the channel model is constructed, and the communication signal of multipath wireless sensor network is recomposed by autocorrelation matched filter detection technology. The time-frequency flipping characteristic of the output signals of each wireless sensor network is used to suppress the inter-symbol interference, the adaptive modulation of the signal at the data receiving end of the wireless sensor network is realized, and the focusing gain of the wireless sensor network link is obtained by using the spread spectrum coding modulation method. The modulated signal is sampled at Nyquist frequency, so that the spread spectrum coding characteristic information is extended simultaneously in time domain and frequency domain, and channel equalization is realized. The simulation results show that the proposed algorithm can effectively suppress inter-symbol interference, increase signal output gain, optimize communication network transmission and reduce the bit error rate, the communication quality is improved.
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References
Carbone, P., Katsifodimos, A., Ewen, S., et al.: Apache Flink: stream and batch processing in a single engine. Bull. IEEE Comput. Soc. Tech. Comm. Data Eng. 36(4), 28–38 (2015)
Lee, Y.Y., Wang, C.H., Huang, Y.H.: A hybrid RF/Baseband Precoding Processor based on Parallel-Index- Selection Matrix-Inversion-Bypass Simultaneous Orthogonal Matching Pursuit for Millimeter Wave MIMO Systems. IEEE Trans. Signal Process. 63(2), 305–317 (2015)
Wang, S., Tu, H., Zhang, Y.: Cloud service composition method based on uncertain QoS-aware Ness. J. Comput. Appl. 38(10), 2753–2758 (2018)
Moradi, M., Keyvanpour, M.R.: An analytical review of XML association rules mining. Artif. Intell. Rev. 43(2), 277–300 (2015)
Dong, G.L., Ryu, K.S., Bashir, M., et al.: Discovering medical knowledge using association rule mining in young adults with acute myocardial infarction. J. Med. Syst. 37(2), 1–10 (2013)
Khalili, A., Sami, A.: SysDetect:a Systematic Approach to Critical State Determination for Industrial Intrusion Detection Systems Using Apriori Algorithm. J. Process Control 2776, 154–160 (2015)
Ju, C.H., Zou, J.B.: An incremental classification algorithm for data stream based on information entropy diversity measure. Telecommun. Sci. 31(2), 86–96 (2015)
Lyu, Y.X., Wang, C.Y., Wang, C., et al.: Online classification algorithm for uncertain data stream in big data. J. Northeast. Univ. (Nat. Sci. Ed.) 37(9), 1245–1249 (2016)
Huang, S.C., Liu, Y.: Classification algorithm for noisy and dynamic data stream. J. Jiangsu Univ. Sci. Technol. (Nat. Sci. Ed.) 30(3), 281–285 (2016)
Ani, L., Xiao, Z., Boyang, Z., Chunyi, L., Xiaonan, Z.: Research on performance evaluation method of public cloud storage system. J. Comput. Appl. 37(5), 1229–1235 (2017)
Lin, J.M., Ban, W.J., Wang, J.Y., et al.: Query optimization for distributed database based on parallel genetic algorithm and max-min ant system. J. Comput. Appl. 36(3), 675–680 (2016)
Zhou, X.P., Zhang, X.F., Zhao, X.N.: Cloud storage performance evaluation research. Comput. Sci. 41(4), 190–194 (2014)
He, S.M., Kang, M.N., Zhang, X., et al.: Cloud storage performance evaluation technology and method research. Comput. Mod. 12, 1–4 (2011)
Tang, K.Z., Li, H.Y., Li, J., et al.: Improved particle swarm optimization algorithm for solving complex optimization problems. J. Nanjing Univ. Sci. Technol. 39(4), 386–391 (2015)
Jia, D.Y., Zhang, F.Z.: A collaborative filtering recommendation algorithm based on double neighbor choosing strategy. J. Comput. Res. Dev. 50(5), 1076–1084 (2013)
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State Grid Tianjin Electric Power Company Science and technology project funding - Internet of things security access system based on NB-IOT (No. KJ19-1-32).
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Liu, H., Liu, Y., Zhang, C., Zheng, Y. (2021). Communication Network Transmission Optimization Algorithm. In: Sugumaran, V., Xu, Z., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2020. Advances in Intelligent Systems and Computing, vol 1233. Springer, Cham. https://doi.org/10.1007/978-3-030-51431-0_57
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DOI: https://doi.org/10.1007/978-3-030-51431-0_57
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