Call drop minimization using Fuzzy associative memory

In this paper, a Fuzzy associative memory approach is adopted to minimize the effect of drop calls in wireless cellular networks. To implement this approach, a number of factors that contribute to call dropping in CDMA networks were identified and data for these factors collected from an operational telecommunication carrier. These data were then used to establish the membership functions for driving the fuzzy inference engine, and through extensive simulations, the overall efficiencies for the existing and optimized forms of the system were obtained. It was observed that as the traffic got burstier, the existing system failed, compared to the optimized system which sustained the efficiency at about 72%. Furthermore, the optimized system exhibited fair allocation of system resources, effectively managing processes such as handovers, and, precluding unnecessary wastage of the system resources. The performance of the optimized system, however, degraded when the drop call probability exceeded the recommended threshold of 0.02. In practical systems, this constraint is obligatory to avert severe network degradation. The interactive effect of the selected factors on the network efficiency was also investigated. We observed the independence of some of these factors, as the drop call probability and system efficiency remained unchanged. But as more channels became available for the growing number of users., there was need for optimal configuration settings to avert scenarios that may negatively impact on the overall system performance.