Abstract
Recently, efficient spectrum estimation has become a fundamental requirement for any wireless communication technology. Accurate detection of spectrum in a populated and noisy environment reduces spectrum scarcity problem. Even though theoretical formulation is sufficient, physical realization and its real-time performance analysis are rare to find out. So, in this work we have investigated thoroughly the autoregressive (AR) modelling of a received signal using Yule-Walker (YW) method with the concept of confidence interval (CI) and Levinson–Durbin algorithm (LDA). The received signal strength has been observed extensively with variations of different radio gain parameters, data length and lag order along with the statistical analysis. Nonlinear curve fitting technique has been used to characterize the correlation between them. The physical study and real-time application of these algorithms have been implemented and verified on an FPGA-based platform by Rice University’s Wireless Open-Access Research Platform test bed in association with WARPLab.
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Chakraborty, D., Sanyal, S.K. (2020). WARP Test Bed Implementation of Lag Order and Data Length-optimized AR Spectrum Estimation Algorithm. In: Maharatna, K., Kanjilal, M., Konar, S., Nandi, S., Das, K. (eds) Computational Advancement in Communication Circuits and Systems. Lecture Notes in Electrical Engineering, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-13-8687-9_18
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DOI: https://doi.org/10.1007/978-981-13-8687-9_18
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