Handoffs Decision Optimization in Mobile Cellular Networks

A neural network (NN) approach is proposed in this paper to optimize the operation of cellular networks. First, we derive an analytical equation to establish the effect of essential handoff contributory factors. Data of these factors were then obtained from base stations of an operational network carrier, and trained on a backpropagation NN algorithm. Results obtained revealed that the network performance improved with big data and increase in number of neurons for SINR data, but, increasing the number of layers degraded the system performance. However, with relative signal strength data, improved performance was achieved for big data and increase in number of layers for normalized and un-normalized data. Finally, self organizing map was explored to visualize the existing system for the purpose of improving further, its performance.