Autors: Marinova, G. I., Bozhinova, K.G.
Title: Study for Randomness of Diverse Pseudo-Random Bit Generators Oriented to Telecommunication Applications
Keywords: Kasami, LFSR, Mersenne twisters, NIST test suite for randomness, PRBGs

Abstract: The paper presents the results from the research for randomness of 8 pseudo random bit generators (PRBGs) for short sequences (256, 512 and 1024 bits) - Linear Feedback Serial Registers (LFSRs) with 8, 9, 16, 21 bits and different taps, Galois, Kasami, Gold and Mersenne-Twister (used in MATLAB). The goal is to determine the best PRBGs for telecommunications implementations for which randomness is critical as Analog-to-Information Converters (AICs) based on compressive sensing, where the recovery of the signal samples at under-Nyquist rate uses a random bit sequence. The PRBGs are tested with 10 tests from NIST suite for randomness which are applicable for short sequences. The PRBGs passing the tests are implemented in a laboratory set-up of AIC for obtaining the solution with the highest Signal-to-Noise and Distortion (SINAD)



    2019 14th International Conference on Advanced Technologies, Systems and Services in Telecommunications, TELSIKS 2019 - Proceedings. Faculty of Electronic Engineering, University of NisNis; Serbia; 23 October 2019 through 25 October 2019, vol. TELSIKS 2019, pp. 224-227 ; Article number 9002014, 2019, Serbia, IEEE Inc, DOI 10.1109/TELSIKS46999.2019.9002014

    Copyright IEEE Inc

    Цитирания (Citation/s):
    1. R. Hegadi and A. P. Patil, "A Statistical Analysis on In-Built Pseudo Random Number Generators Using NIST Test Suite," 2020 5th International Conference on Computing, Communication and Security (ICCCS), 2020, pp. 1-6, doi: 10.1109/ICCCS49678.2020.9276849. - 2020 - в издания, индексирани в Scopus или Web of Science
    2. Hui Zong, Zining Cao, Jianyang Zhao and Yuanzhou Zhu, Evaluation of periodic characteristics of pseudo-random number generator, World Scientific Proceedings Series on Computer Engineering and Information ScienceDevelopments of Artificial Intelligence Technologies in Computation and Robotics, pp. 317-324 (2020)No Access, This work is supported by the National Natural Science Foundation of China under Grant No. 61170322. - 2020 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus