Abstract
An approaching to the transmission channel capacity with a limited frequency band ΔF is achieved by using signals with length Ts exceeding the duration of the symbol’s transmission interval T. Such signals are transmitted under conditions of significant intersymbol interference. This leads to the fact that a random sequence of transmitted signals will have significant values of the peak to average power ratio (PAPR). To estimate the value of PAPR, it is necessary to determine the statistical characteristics of the random process emission. This will help to form the conditions for the permissible amplitude limitation of the output signal. In the work we find probability distributions of instantaneous amplitude values of the random optimal signal sequences with different durations (Ts = 8T…16T). The conditions for approximating the distribution histograms to the Gaussian process are found. As a information source, a Gaussian source with quantization of levels of sampled values was selected. It is shown that with the number of quantization levels exceeding 32, the histograms approach a truncated Gaussian distribution. Simulation results are given for the transmission speed of the channel alphabet symbols from R = 1/T to R = 10/T, which corresponds to the faster-than-Nyquist transmission rate. Recommendations are given on the required dynamic range of operation for power amplifiers in transmitting devices in accordance with the obtained value of FTN signal sequences PAPR.
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Acknowledgment
This research work was supported by Peter the Great St. Petersburg Polytechnic University in the framework of the Program “5-100-2020” and used computational resources of Peter the Great Saint-Petersburg Polytechnic University Supercomputing Center (http://www.scc.spbstu.ru).
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Lavrenyuk, I., Makarov, S.B., Hu, B., Dong, G., Kudryashova, T. (2020). Probability Distributions of Instantaneous Amplitude Values of Random Optimal FTN Signal Sequences with Controlled ISI. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2020 2020. Lecture Notes in Computer Science(), vol 12526. Springer, Cham. https://doi.org/10.1007/978-3-030-65729-1_11
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