resource management in 3g networks using case-based reasoning
This paper proposes a new method of balancing traffic load in mobile cellular networks by using Case-Based Reasoning (CBR) to learn traffic patterns at periods of congestion, the obtained traffic patterns then being used to control co-operating semi-smart antennas to optimise the radio coverage, hence minimising the effects of the congestion. Unlike previous work, this scheme does not require calculating the optimum patterns each time. The emphasis of this paper is to demonstrate case matching of congestion by CBR with a particular study of the sensitivity to the similarity function.
case-based reasoning (cbr) learning matching wcdma geographical load balancing