Prediction of antenna patterns for hotspots in WCDMA Networks

This paper proposes a new method of balancing traffic load in mobile cellular networks and predicting the change of radio coverage to prevent congestion in advance. Case-Based Reasoning (CBR) is used to learn traffic patterns at periods of congestion and to apply the most suitable antenna patterns when a similar traffic pattern reappears. Unlike previous work, this scheme does not require calculating the optimum patterns each time, hence the computational complexity is greatly reduced. In addition, CBR also provides the capability of congestion prediction. Simulations have been performed to evaluate the system performance for different traffic scenarios, and the results are presented.