An Overview of Call Admission Control in Mobile Cellular Networks

Cava Wine Authentication Employing a Voltammetric Electronic Tongue

“…However, the main difference lies in the fact that LDA explicitly attempts to model the difference between the classes of data; while PCA does not take into account any difference between classes, providing only a visualization of the variability of the data, not implying any clustering of it, although formation of groups of samples can be a possible result. That is, LDA involves the use of a supervised method instead of an unsupervised one in the machine learning task 26. For this reason, PCA is normally used just as a visualization tool that permits to check if the samples group together in classes, and cannot be considered as a properly pattern recognition method; whereas to be used as a classifier it must be coupled with a modeling tool such as ANNs.…”

Cellular and Wi-Fi technologies evolution: from complementarity to competition

“…CAC in general in cellular networks deals with an automatic decision whether a call will be served or blocked while trying to avoid the droppings. As such, CAC represents one of the most essential methods for optimal resource management [152]. The CAC decision is determined by studying several dynamic parameters of the network, pertaining to existing network resources and their utilization.…”

“…For this reason, an LTE CAC scheme relying on a learning-based approach, which can react to the actual conditions faced by each cell, looks more promising. In [152], the authors formulate the CAC as a constrained optimization problem and solve it by leveraging a Genetic Algorithm. The advantage of this algorithm is that it gives a complete view of the network and considers various dynamic network parameters.…”