<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">tuzsut</journal-id><journal-title-group><journal-title xml:lang="ru">Труды учебных заведений связи</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of Telecommunication Universities</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1813-324X</issn><issn pub-type="epub">2712-8830</issn><publisher><publisher-name>СПбГУТ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.31854/1813-324X-2025-11-3-47-58</article-id><article-id custom-type="edn" pub-id-type="custom">OJBGGT</article-id><article-id custom-type="elpub" pub-id-type="custom">tuzsut-685</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ЭЛЕКТРОНИКА, ФОТОНИКА, ПРИБОРОСТРОЕНИЕ И СВЯЗЬ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ELECTRONICS, PHOTONICS, INSTRUMENTATION AND COMMUNICATIONS</subject></subj-group></article-categories><title-group><article-title>Распределение комплексной огибающей сигналов, принятых из канала в условиях «сложной» сигнально-помеховой обстановки</article-title><trans-title-group xml:lang="en"><trans-title>Distribution of the Complex Envelope for Signals Received from a Channel with a "Complex" Signal-Noise Environment</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8989-8122</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Маслаков</surname><given-names>М. Л.</given-names></name><name name-style="western" xml:lang="en"><surname>Maslakov</surname><given-names>M. L.</given-names></name></name-alternatives><bio xml:lang="ru"><p>кандидат технических наук, старший научный сотрудник отдела РМ ВЧ ООО «Специальный технологический центр», доцент кафедры инфокоммуникационных технологий и систем связи Санкт-Петербургского государственного университета аэрокосмического приборостроения</p></bio><email xlink:type="simple">maslakov.ml@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">ООО «Специальный Технологический Центр»; Санкт-Петербургский государственный университет аэрокосмического приборостроения<country>Россия</country></aff><aff xml:lang="en">LLC Special Technology Center; Saint-Petersburg State University of Aerospace Instrumentation<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>08</day><month>07</month><year>2025</year></pub-date><volume>11</volume><issue>3</issue><fpage>47</fpage><lpage>58</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Маслаков М.Л., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Маслаков М.Л.</copyright-holder><copyright-holder xml:lang="en">Maslakov M.L.</copyright-holder><license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://tuzs.sut.ru/jour/article/view/685">https://tuzs.sut.ru/jour/article/view/685</self-uri><abstract><sec><title>Аннотация</title><p>Аннотация. При статистическом анализе комплексных огибающих модулированных сигналов, принимаемых из канала связи, в качестве модели плотности распределения вероятностей общепринято полагают нормальную плотность распределения. Однако в канале с глубокими замираниями, а также при наличии помех, т. е. в случае «сложной» сигнально-помеховой обстановки, интерес могут представлять модели распределений, обладающие более тяжелыми хвостами. В качестве таковых в работе рассматриваются логистическое распределение и распределение гиперболического секанса. В работе приведены выражения для соответствующих двумерных плотностей распределения вероятностей.</p></sec><sec><title>Цель работы</title><p>Цель работы: показать, что при определенных условиях в реальном канале связи могут наблюдаться модели распределения комплексной огибающей, отличные от нормального. Учет данного обстоятельства может позволить улучшить характеристики системы связи в задачах адаптации и оценки надежности решений демодулятора.</p></sec><sec><title>Методы исследования</title><p>Методы исследования: для проверки принадлежности комплексной огибающей соответствующему закону распределения применяется критерий Хи-квадрат. В статье предложена реализация критерия Хи-квадрат для случая двумерной плотности распределения. </p><p>В качестве результатов в работе представлен анализ статистической обработки сигналов, принятых из реального канала связи в различных условиях.</p><p>Новизна состоит в экспериментальном исследовании факта, что в реальных каналах в случае глубоких замираний и сложной сигнально-помеховой обстановки более предпочтительными могут оказаться логистическое распределение или распределение гиперболического секанса.</p><p>Практическая значимость заключается в том, что учет модели распределения позволяет получить более адекватную оценку среднего квадратичного отклонения шумовой составляющей и отношения сигнал / шум, что имеет существенное значение для функционирования адаптивных систем радиосвязи, а также в задаче оценки мягких решений демодуляции.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Relevance</title><p>Relevance. In statistical analysis of complex envelopes of modulated signals received from a communication channel, the normal distribution density is generally assumed to be the probability density model. However, in a channel with deep fading and in the presence of interference, i.e. in the case of a "complex" signal-interference environment in the channel, distribution models with heavier tails may be of interest. The logistic distribution and the hyperbolic secant distribution are considered as such in the work. Expressions for the corresponding two-dimensional probability distribution densities are presented.</p><p>The aim of the work is to show that, under certain conditions, models of the distribution of the complex envelope that other than normal one can be observed in a real communication channel. Taking this into account may allow to improve the characteristics of the communication system in the tasks of adaptation and evaluation of the reliability of demodulator solutions.</p></sec><sec><title>Research methods</title><p>Research methods: To check whether the complex envelope belongs to the corresponding distribution law, the Chi-square criterion is used. The implementation of the Chi-square criterion for the case of a two-dimensional distribution density is proposed in article.</p><p>As results, the paper presents the analysis of statistical processing of signals received from a real communication channel under various conditions.</p><p>The novelty lies in the experimental study of the fact that in real channels, in the case of deep fading and complex signal-interference conditions, the logistic distribution or the hyperbolic secant distribution may be more preferable.</p><p>The practical significance lies in the fact that taking into account the distribution model makes it possible to obtain a more adequate estimate of the mean square deviation of the noise component and the signal-to-noise ratio, which is essential for the functioning of adaptive radio communication systems, as well as in the task of evaluating soft demodulation solutions.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>комплексная огибающая</kwd><kwd>двумерное нормальное распределение</kwd><kwd>двумерное логистическое распределение</kwd><kwd>двумерное распределение гиперболического секанса</kwd><kwd>критерий Хи-квадрат</kwd><kwd>отношение сигнал / шум</kwd></kwd-group><kwd-group xml:lang="en"><kwd>complex envelope</kwd><kwd>2-dimensional normal distribution</kwd><kwd>2-dimensional logistic distribution</kwd><kwd>2-dimensional hyperbolic secant distribution</kwd><kwd>chi-squared test</kwd><kwd>signal-to-noise ratio</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Levy B.C. Principles of Signal Detection and Parameter Estimation. New York: Springer, 2008. DOI:10.1007/978-0-387-76544-0</mixed-citation><mixed-citation xml:lang="en">Levy B.C. Principles of Signal Detection and Parameter Estimation. New York: Springer; 2008. DOI:10.1007/978-0-387-76544-0</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Barkat M. Signal Detection and Estimation. Boston: Artech, 2005.</mixed-citation><mixed-citation xml:lang="en">Barkat M. Signal Detection and Estimation. Boston: Artech; 2005.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Серкин Ф.Б., Важенин Н.А., Вейцель В.В. Сравнительный анализ алгоритмов оценки отношения сигнал-шум на основе квадратурных компонент принимаемого сигнала // Труды МАИ. 2015. № 83. C. 19. EDN:UNWXRT</mixed-citation><mixed-citation xml:lang="en">Serkin F.B., Vazhenin N.A., Veytsel V.V. Analysis of signal-to-noise ratio estimation algorithms based on inphase and quadrature components of the received signal. Trudy MAI. 2015;83:19. (in Russ.) EDN:UNWXRT</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Beaulieu N.C., Toms A.S., Pauluzzi D.R. Comparison of four SNR estimators for QPSK modulations // IEEE Communications Letters. 2000. Vol. 4. Iss. 2. PP. 43‒45. DOI:10.1109/4234.824751</mixed-citation><mixed-citation xml:lang="en">Beaulieu N.C., Toms A.S., Pauluzzi D.R. Comparison of four SNR estimators for QPSK modulations. IEEE Communications Letters. 2000;4(2):43‒45. DOI:10.1109/4234.824751</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Pauluzzi D.R., Beaulieu N. A comparison of SNR estimation techniques in the AWGN channel // Proceedings of the Pacific Rim Conference on Communications, Computers, and Signal Processing (Victoria, Canada, 17‒19 May 1995). IEEE, 1995. DOI:10.1109/PACRIM.1995.519404</mixed-citation><mixed-citation xml:lang="en">Pauluzzi D.R., Beaulieu N. A comparison of SNR estimation techniques in the AWGN channel. Proceedings of the Pacific Rim Conference on Communications, Computers, and Signal Processing, 17‒19 May 1995, Victoria, Canada. IEEE; 1995. DOI:10.1109/PACRIM.1995.519404</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Cavers J.K. Mobile Channel Characteristics. New York: Kluwer, 2002.</mixed-citation><mixed-citation xml:lang="en">Cavers J.K. Mobile Channel Characteristics. New York: Kluwer; 2002.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Тихонов В.И. Статистическая радиотехника. М.: Советское радио, 1966.</mixed-citation><mixed-citation xml:lang="en">Tikhonov V.I. Statisticheskaya radiotekhnika. Moscow: Sovetskoe radio Publ.; 1966. (in Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Simon M.K., Alouini M.S. Digital Communication over Fading Channels: A Unified Approach to Performance Analysis. New York: John Wiley &amp; Sons, 2000.</mixed-citation><mixed-citation xml:lang="en">Simon M.K., Alouini M.S. Digital Communication over Fading Channels: A Unified Approach to Performance Analysis. New York: John Wiley &amp; Sons; 2000.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Патюков В.Г., Патюков Е.В., Силантьев А.А. Оценка отношения сигнал/шум на основе фазовых флуктуаций сигнала // Журнал радиоэлектроники. 2013. № 4. С. 1. EDN:PZZBWL</mixed-citation><mixed-citation xml:lang="en">Patyukov V.G., Patyukov E.V., Silantiev A.A. Measurement of the attitude a signal/noise on the basis of phase fluctuations of a signal. Journal of Radio Electronics. 2013;4:1. (in Russ.) EDN:PZZBWL</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Jammalamadaka S.R., Sengupta A. Topics in Circular Statistics. Singapore: World Scientific, 2001.</mixed-citation><mixed-citation xml:lang="en">Jammalamadaka S.R., Sengupta A. Topics in Circular Statistics. Singapore: World Scientific; 2001.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Mardia K.V., Jupp P.E. Directional Statistics. John Wiley &amp; Sons, Inc, 2000.</mixed-citation><mixed-citation xml:lang="en">Mardia K.V., Jupp P.E. Directional Statistics. John Wiley &amp; Sons, Inc; 2000.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Tong Y.L. The Multivariate Normal Distribution. New-York: Springer-Verlag, 1990.</mixed-citation><mixed-citation xml:lang="en">Tong Y.L. The Multivariate Normal Distribution. New-York: Springer-Verlag; 1990.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Thomas C.M. Maximum Likelihood Estimation of Signal-to-Noise Ratio. Ph.D. Thesis. Los Angeles: University of Southern California, 1967.</mixed-citation><mixed-citation xml:lang="en">Thomas C.M. Maximum Likelihood Estimation of Signal-to-Noise Ratio. Ph.D. Thesis. Los Angeles: University of Southern California; 1967.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Bellili F., Meftehi R., Affes S., Stephenne A. Maximum likelihood SNR estimation over time-varying flat-fading SIMO channels // Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP, Florence, Italy, 04-09 May 2014). IEEE, 2014. PP. 6523‒6527. DOI:10.1109/ICASSP.2014.6854861</mixed-citation><mixed-citation xml:lang="en">Bellili F., Meftehi R., Affes S., Stephenne A. Maximum likelihood SNR estimation over time-varying flat-fading SIMO channels. Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP, 04‒09 May 2014, Florence, Italy. IEEE; 2014. p.6523‒6527. DOI:10.1109/ICASSP.2014.6854861</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Treviño J.C., Benammar M., Roque D. A Hybrid Envelope-IQ Moment-Based Non-Data-Aided SNR Estimator for QPSK // IEEE Communications Letters. 2024. Vol. 28. Iss. 6. PP. 1382‒386. DOI:10.1109/LCOMM.2024.3386188</mixed-citation><mixed-citation xml:lang="en">Treviño J.C., Benammar M., Roque D. A Hybrid Envelope-IQ Moment-Based Non-Data-Aided SNR Estimator for QPSK. IEEE Communications Letters. 2024;28(6):1382‒1386. DOI:10.1109/LCOMM.2024.3386188</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Силантьев А.А., Шатров В.А., Патюков В.Г., Рябушкин С.А. Метод оценки отношения сигнал/шум на основе статистических характеристик выбросов случайных процессов применительно к командно-измерительной системе спутниковой связи // Исследования Наукограда. 2014. № 4(10). С. 4‒8. EDN:TBSMSV</mixed-citation><mixed-citation xml:lang="en">Silantyev A.A., Shatrov V.A., Patyukov V.G., Ryabushkin S.A. Method of estimation of the signal/noise ratio, based on the statistical characteristics of the emission of stochastic processes, as applied to the telemetry, commandand ranging system of satellite communication. Issledovaniya Naukograda. 2014;4(10):4‒8. (in Russ.) EDN:TBSMSV</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Агеев Ф.И., Вознюк В.В., Куценко Е.В. Методика расчета вероятности ошибки оптимального посимвольного когерентного приема MPSK сигналов при наличии в канале радиосвязи узкополосной шумовой помехи // Труды МАИ. 2024. № 139. С. 15. EDN:QBDQJZ</mixed-citation><mixed-citation xml:lang="en">Ageev F.I., Voznuk V.V., Kutsenko E.V. A method for calculating the probability of a bit error of optimal character-by-character coherent reception of multiple phase-manipulated signals in the presence of narrowband noise interference in the radio communication channe. Trudy MAI. 2024;139:15. (in Russ.) EDN:QBDQJZ</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Bakkali M., Stephenne A., Affes S. Iterative SNR Estimation for MPSK Modulation Over AWGN Channels // Proceedings of the Vehicular Technology Conference (Montreal, Canada, 25‒28 September 2006). IEEE, 2006. DOI:10.1109/VTCF.2006.350</mixed-citation><mixed-citation xml:lang="en">Bakkali M., Stephenne A., Affes S. Iterative SNR Estimation for MPSK Modulation Over AWGN Channels. Proceedings of the Vehicular Technology Conference, 25‒28 September 2006, Montreal, Canada. IEEE; 2006. DOI:10.1109/VTCF.2006.350</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Jiang L., Zheng G., Zhang B. A Noise Estimation Method Based on Envelope Pseudo-measurement System in Adaptive Kalman Filter // Proceedings of the 43rd Chinese Control Conference (CCC, Kunming, China, 28‒31 July 2024). IEEE, 2024. PP. 208‒213. DOI:10.23919/CCC63176.2024.10661809</mixed-citation><mixed-citation xml:lang="en">Jiang L., Zheng G., Zhang B. A Noise Estimation Method Based on Envelope Pseudo-measurement System in Adaptive Kalman Filter. Proceedings of the 43rd Chinese Control Conference, CCC, 28‒31 July 2024, Kunming, China. IEEE; 2024. p.208‒213. DOI:10.23919/CCC63176.2024.10661809</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Türkben Ö.Ü.A.K., Al-Akraa V. S.A. SNR Estimation in Communication Systems Using Cognitive Radio // Proceedings of the 5th International Conference on Engineering Technology and its Applications (IICETA, Al-Najaf, Iraq, 31 May ‒ 01 June 2022). IEEE, 2022. PP. 477‒481. DOI:10.1109/IICETA54559.2022.9888467</mixed-citation><mixed-citation xml:lang="en">Türkben Ö.Ü.A.K., Al-Akraa V. S.A. SNR Estimation in Communication Systems Using Cognitive Radio. Proceedings of the 5th International Conference on Engineering Technology and its Applications, IICETA, 31 May ‒ 01 June 2022, Al-Najaf, Iraq. IEEE; 2022. p.477‒481. DOI:10.1109/IICETA54559.2022.9888467</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Лемешко Б.Ю., Лемешко С.Б., Постовалов С.Н., Чимитова Е.В. Статистический анализ данных, моделирование и исследование вероятностных закономерностей. Компьютерный подход. Новосибирск: Изд-во НГТУ, 2011. EDN:TZNHMX</mixed-citation><mixed-citation xml:lang="en">Lemeshko B.Yu., Lemeshko S.B., Postovalov S.N., Chimitova E.V. Statistical data Analysis, Simulation and Study of Probability Regularities. Computer Approach. Novosibirsk: NSTU Publ.; 2011. (in Russ.) EDN:TZNHMX</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Balakrishnan N. Handbook of the Logistic Distribution. Boca Raton: CRC Press, 1991. 624 p. DOI:10.1201/9781482277098</mixed-citation><mixed-citation xml:lang="en">Balakrishnan N. Handbook of the Logistic Distribution. Boca Raton: CRC Press; 1991. 624 p. DOI:10.1201/9781482277098</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Giri N.C. Multivariate Statistical Analysis. Boca Raton: Marcel Dekker, 2003. 550 p. DOI:10.1201/9781482276374</mixed-citation><mixed-citation xml:lang="en">Giri N.C. Multivariate Statistical Analysis. Boca Raton: Marcel Dekker; 2003. 550 p. DOI:10.1201/9781482276374</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Fischer M.J. Generalized Hyperbolic Secant Distributions. New York: Springer, 2014. DOI:10.1007/978-3-642-45138-6</mixed-citation><mixed-citation xml:lang="en">Fischer M.J. Generalized Hyperbolic Secant Distributions. New York: Springer; 2014. DOI:10.1007/978-3-642-45138-6</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Капля Е.В. Обобщение закона гиперболического секанса и логистического закона распределения в единый закон распределения с варьируемым коэффициентом эксцесса // Дальневосточный математический журнал. 2020. Т. 20. № 1. С. 74‒81. DOI:10.47910/FEMJ202008. EDN:NLRAHN</mixed-citation><mixed-citation xml:lang="en">Kaplya E.V. The generalization of the hyperbolic secant distribution and the logistic distribution in the single dostribution with variable kurtosis. Far Eastern Mathematical Journal. 2020;20(1):74–81. (in Russ.) DOI:10.47910/FEMJ202008. EDN:NLRAHN</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Ding P. Three Occurrences of the Hyperbolic-Secant Distribution // The American Statistician. 2014. Vol. 68. Iss. 1. PP. 32‒35. DOI:10.1080/00031305.2013.867902</mixed-citation><mixed-citation xml:lang="en">Ding P. Three Occurrences of the Hyperbolic-Secant Distribution. The American Statistician. 2014;68(1):32‒35. DOI:10.1080/00031305.2013.867902</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Forbes C., Evans M., Hastings N., Peacock B. Statistical Distributions. New Jersey: John Wiley &amp; Sons, 2011. 230 p.</mixed-citation><mixed-citation xml:lang="en">Forbes C., Evans M., Hastings N., Peacock B. Statistical Distributions. New Jersey: John Wiley &amp; Sons; 2011. 230 p.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Greenwood P.E., Nikulin M.S. A Guide to Chi-Squared testing. New York: John Wiley &amp; Sons, 1996. 304 p.</mixed-citation><mixed-citation xml:lang="en">Greenwood P.E., Nikulin M.S. A Guide to Chi-Squared testing. New York: John Wiley &amp; Sons; 1996. 304 p.</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Никулин М.С. О критерии согласия Хи-квадрат для непрерывных распределений с параметрами сдвига и масштаба // Теория вероятностей и ее применение. 1973. Т. 18. № 3. С. 583‒591.</mixed-citation><mixed-citation xml:lang="en">Nikulin M.S. Chi-Square Test for Continuous Distributions with Shift and Scale Parameters Theory of Probability and its Applications. 1974;18(3):559‒568. DOI:10.1137/1118069</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Watson G.S. On Chi-Square Goodness-of-Fit Tests for Continuous Distributions // Journal of the Royal Statistical Society: Series B. 1958. Vol. 20. Iss. 1. PP. 44‒61. DOI:10.1111/j.2517-6161.1958.tb00274.x</mixed-citation><mixed-citation xml:lang="en">Watson G.S. On Chi-square goodness-of-fit tests for continuous distributions. Journal of the Royal Statistical Society: Series B. 1958;20(1):44‒61. DOI:10.1111/j.2517-6161.1958.tb00274.x</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Мирвалиев М. Критерии согласия Хи-квадрат для одного семейства многомерных дискретных распределений // Теория вероятностей и ее применение. 1989. Т. 34. № 4. С. 794‒799.</mixed-citation><mixed-citation xml:lang="en">Mirvaliev M. Chi-Square Goodness-of-Fit Tests for a Family of Multidimensional Discrete Distributions. Theory of Probability and its Applications. 1989;34(4):728‒732. DOI:10.1137/1134094</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Воинов В.Г., Никулин М.С. Критерий согласия Хи-квадрат для одномерных и многомерных дискретных распределений // Записки научных семинаров ЛОМИ. 1990. Т. 184. С. 62‒79.</mixed-citation><mixed-citation xml:lang="en">Voinov V.G., Nikulin M.S. Chi-square goodness-of-fit test for one- and multidimensional discrete distributions. Journal of Mathematical Sciences. 1994;68:438‒450. DOI:10.1007/BF01254268</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Лемешко Б.Ю., Чимитова Е.В. О выборе числа интервалов в критериях согласия типа С2 // Заводская лаборатория. Диагностика материалов. 2003. Т. 69. № 1. С. 61‒67. EDN:SDJQIF</mixed-citation><mixed-citation xml:lang="en">Lemeshko B.Yu., Chimitova E.V. On the choice of the number of intervals in Type C2 Good-Affirmation Criteria. Zavodskaya laboratoriya. Diagnostika materialov. 2003:69(1):61‒67. (in Russ.) EDN:SDJQIF</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Hasan A.A., Marsland I.D. Low Complexity LLR Metrics for Polar Coded QAM // Proceedings of the 30th Canadian Conference on Electrical and Computer Engineering (CCECE, Windsor, Canada, 30 April ‒ 03 May 2017). IEEE, 2017. DOI:10.1109/CCECE.2017.7946778</mixed-citation><mixed-citation xml:lang="en">Hasan A.A., Marsland I.D. Low Complexity LLR Metrics for Polar Coded QAM. Proceedings of the 30th Canadian Conference on Electrical and Computer Engineering, CCECE, 30 April ‒ 03 May 2017, Windsor, Canada. IEEE; 2017. DOI:10.1109/ CCECE.2017.7946778</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru"></mixed-citation><mixed-citation xml:lang="en"></mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
