TY - GEN
T1 - Influence of Transmission Path Randomness on Terminal Reflection Characteristics
AU - Bai, Ruimin
AU - Peng, Zhenzhen
AU - Yu, Ze
AU - Li, Bing
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/7
Y1 - 2020/12/7
N2 - An approximate method is introduced to predict the distribution of source reflection coefficient when transmission path with stochastic height above ground in any position. The transmission path is divided into many segments, assuming that the height of each segment is independent and identically distributed. When the height is logarithmic normal distributed, expression of mean value and variance are derived, the values are referred to as calculated value. Meanwhile, the accurate expression of source reflection coefficient is obtained based on transmission line theory, then the mean value and variance are calculated in a statistical way by calculating the source reflection coefficient thousands of times. The values are referred to as statistical value. Moreover, the comparison between the statistical value and the calculated value shows the validity and the benefit of this approach. With the number of segments increase, the approximate method is more accurate. What is more, the calculated value consists well with the statistical value in a wide frequency range. Compared with the other statistical method, the approximate method is easier and more feasible.
AB - An approximate method is introduced to predict the distribution of source reflection coefficient when transmission path with stochastic height above ground in any position. The transmission path is divided into many segments, assuming that the height of each segment is independent and identically distributed. When the height is logarithmic normal distributed, expression of mean value and variance are derived, the values are referred to as calculated value. Meanwhile, the accurate expression of source reflection coefficient is obtained based on transmission line theory, then the mean value and variance are calculated in a statistical way by calculating the source reflection coefficient thousands of times. The values are referred to as statistical value. Moreover, the comparison between the statistical value and the calculated value shows the validity and the benefit of this approach. With the number of segments increase, the approximate method is more accurate. What is more, the calculated value consists well with the statistical value in a wide frequency range. Compared with the other statistical method, the approximate method is easier and more feasible.
KW - source reflection coefficient
KW - statistical method
KW - stochastic height
KW - transmission line theory
UR - https://www.scopus.com/pages/publications/85101285883
U2 - 10.1109/NEMO49486.2020.9343575
DO - 10.1109/NEMO49486.2020.9343575
M3 - 会议稿件
AN - SCOPUS:85101285883
T3 - 2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020
BT - 2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020
Y2 - 7 December 2020 through 9 December 2020
ER -