Cognitive Radio Resource Management for Improving the Efficiency of LTE Network Segments in the Wireless B3G World

In this paper, we provide a framework for enhancing radio resource management (RRM) in 3G long term evolution (LTE) systems with cognitive features. By exploiting the capabilities of orthogonal frequency division multiplexing (OFDM) LTE access technology, network segments are capable of properly adapting to the environment conditions by applying RRM algorithms for optimized sub-carriers' assignment, power allocation and adaptive modulation. On the other hand, cognitive features can be used to provide the system with knowledge that derives from past interactions with the environment. As a result, the system will be able to apply already known solutions in timely manner when identifying a problem that has been already addressed in the past. Framed within the above statements, we propose and validate a cognitive RRM scheme in the context of LTE network segments. Indicative examples and results showcase that the proposed scheme can result in significant efficiency improvement in terms of performance and network adaptation.