원문정보
국제인공지능학회(구 한국인터넷방송통신학회)
The International Journal of Advanced Smart Convergence
Volume 13 Number 4
2024.12
pp.19-30
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
A Markov-modulated Bernoulli process (MMBP) is a mathematical framework used to describe the state of a system over time, where a binary state (either success or failure) is determined by the environment of the system, which evolves randomly over time according to a discrete-time Markov chain. In this paper, we present an MMBP-based mathematical modeling and analysis for evaluating the performance of the slotted Aloha random access protocol from both terminal and network perspectives. In particular, we investigate channel usage patterns in the presence of fading and present a unified analytic approach that benefits from the MMBPbased modeling. Through numerical studies, we verify the efficacy of our analysis.
목차
Abstract
1. Introduction
2. S-Aloha random access in Gilbert-Elliott channels
3. MMBP-based modeling and analysis [12]
4. MMBP-based modeling of channel usage patterns from a terminal perspective
5. MMBP-based modeling of channel usage patterns from the network perspective
6. Numerical results
6.1 Simulation setup and parameters
6.2 Evaluation of channel usage patterns from a terminal perspective
6.3 Evaluation of channel usage patterns from the network perspective
7. Conclusion
References
1. Introduction
2. S-Aloha random access in Gilbert-Elliott channels
3. MMBP-based modeling and analysis [12]
4. MMBP-based modeling of channel usage patterns from a terminal perspective
5. MMBP-based modeling of channel usage patterns from the network perspective
6. Numerical results
6.1 Simulation setup and parameters
6.2 Evaluation of channel usage patterns from a terminal perspective
6.3 Evaluation of channel usage patterns from the network perspective
7. Conclusion
References
저자정보
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