The unparalleled evolution of wireless communications is reflected in the tremendous investments on research and development, targeted at the continuous introduction of innovations that could serve the information society. This has led to the coexistence and complementary exploitation of versatile, legacy and also emerging Radio Access Technologies (RATs). At the same time, the continuously varying environment/users requirements impose the adaptation of those technologies to external stimuli, through reconfiguration (reconsideration) of their infrastructure and/or operating parameters. One feasible option to tackle the increased complexity of such environments, is to design wireless infrastructures with learning capabilities, thus forming cognitive networks. Cognitive networks are able to retain information from their interactions with the environment and intelligently adapt to any requirements. A prerequisite to facilitate operability of cognitive networks is the development of novel management mechanisms, which need to, distributively (centralized approaches would get even more complex), evaluate changes in external conditions and determine the way in which the network will properly respond to them. To this effect, this paper presents a complete framework under which Cognitive Access Points (CgAPs) could be managed and analyzes the functionality of its entities. Moreover, it also provides an approach for managing Cognitive Wireless Network Segments (CgWNSs).
- Cognitive networks
- Self-Management of Cognitive Access Points (SMCgAP)
- Self-Management of Cognitive Wireless Network Segments (SMCgWNS)