Open AccessPerformance and Optimization of Outage Probability in CBTC Systems
Author(s) -
Do Viet Ha,
Hanoi Communications,
Tu Lam Thanh,
Trịnh Thị Hường,
Trinh Van Chien
Publication year - 2021
Publication title -
international journal of electrical and electronic engineering and telecommunications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.171
H-Index - 6
ISSN - 2319-2518
DOI - 10.18178/ijeetc.10.6.439-447
Subject(s) - fading , computer science , position (finance) , computation , channel (broadcasting) , channel state information , minification , ergodic theory , monte carlo method , mathematical optimization , optimization problem , algorithm , control theory (sociology) , mathematics , telecommunications , wireless , control (management) , statistics , mathematical analysis , finance , artificial intelligence , economics
The performance of two Access Points (APs) Communication-Based Train-Control (CBTC) systems subjected to an imperfect channel state information (CSI) scenario is investigated. More precisely, we first model the realistic small-scale fading distribution for which the receiver only has the outdated CSI due to the mobility of the train. We then derive the Outage Probability (OP) of the train and the ergodic capacity of the system in the closed-form expression based on the considered channel model. Additionally, we formulate an optimization problem that minimizes the maximal OP, which corresponds to the location of the train. For such, the signal-to-noise-ratio (SNR) is minimized as a function of the position of two APs. The pattern search method is utilized to solve the considered minimization problem. Numerical results confirm that by the optimal placement of the position of APs, the OP can be significantly ameliorated compared to the other placement methods. Furthermore, the numerical results also illustrate that the proposed solution completely coincides with the exhaustive search but with much less computation time. Finally, the mathematical framework is verified extensively by Monte Carlo simulations.