期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2012
卷号：2012
DOI：10.1155/2012/878595
出版社：Hindawi Publishing Corporation
摘要：To reduce capital expenditures (CAPEX) and operational expenditures (OPEX) in network operations, self-organizing network (SON) has been introduced as a key part of long-term-evolution (LTE) system. Self-optimization of coverage and capacity is one of the most important tasks in the context of SON. This paper proposes a central control mechanism that utilizes the fuzzy Q-learning algorithm in a decentralized fashion for this task. In our proposed approach, each eNB is a learning agent that tries to optimize its antenna downtilt automatically using information from its own and its neighboring cells, and the initialization and the termination of the optimization processes of all agents are in the control of the central entity. The simulation results verify that our proposed approach can achieve remarkable performance enhancement as well as fast convergence, indicating that it is able to meet different levels of demands defined by 3GPP for coverage and capacity optimization.
