Fuzzy Guided Tabu Search Algorithm (FGTSA) Based Load Balancing in LTE and LTE-A Networks

Abstract

The incredible growth of technical aspects and usage observed in wireless technology is prone to unapparent service provision owing to the magnitude growth of mobile users demanding high bandwidth. The present trend of cellular networks demands the experts intervention in the configuration setup and in the management of the networks. This evinces the high maintenance cost, the time consuming and its risk to failures. Hence the necessity of self-organizing possibilities with minimal experts contribution. The user mobility from one cell boundary to another leads to vary the traffic load on the cell. Hence the load balancing is viewed as critical factor in order to achieve the maximal quality of the service. The load balancing balances the load between overloaded and load free neighboring cells to evince the quality of the service in the context of end user experience. The outburst capacity of self-organizing networks of type LTE and LTE-A forces to achieve an optimized Load balancing. The tuning of handover margins and the optimal selection of cells are critical to achieve the load balancing for next generation networks such as LTE and LTE-A. The critical constraint of the load balancing by tuning the handover margin often leads to call dropping, hence the optimal cell selection is a promising factor to achieve an optimized load balancing. In order to do this, a Fuzzy Guided Tabu Search Algorithm (FGTSA) is proposed in this manuscript for solving the load balancing problem. The objectives such as decreasing the call blocking in congested cells, restricting the call dropping in neighboring cells, according to the network policy, are aimed by the FGTSA model proposed in this manuscript. In particular, the FGTSA optimization is done to accurately preserve the call quality constraint during the load balancing under network variations.