Management of Network and Energy Resources in Cognitive and Self-Organizing Wireless Networks

The reduction of the consumed energy in modern selforganizing communication systems in a dense urban environment is a challenging task that requires coordination in management operations for the most effective use of network resources. Configuration and performance optimization tasks affect energy consumption of specific components and energy-related metrics of different devices. We propose a novel approach for energy saving and resource management in a wireless urban environment. Central to our approach is the organization of WLAN access points into clusters to facilitate local management and coordination. In each cluster, a cluster head access point monitors the energy consumption changes during the transmission and reception, at both the access point and user equipment sides, and decides on the appropriate adaptation action. The energy consumption reduction and performance improvement attained under the proposed solutions, at both the network and the user equipment sides, is evaluated via simulation.