An Architecture for Self-Tuning Cellular Systems

As cellular networks grow in size and complexity, the process of managing them becomes increasingly costly for mobile operators. It is therefore important to focus on simplifying or automating these tasks. This article describes an architecture for real-time performance monitoring and tuning of a cellular network, using event-based statistics. It also presents evaluation results in a field trial at the operator SmarTone in Hong Kong which show that the suggested agent/task pattern is well suited to implementing self-tuning algorithms.