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a b s t r a c tIn this paper, we propose a self-optimized coverage function for LTE femtocells embedded in a macrocell area. Each Femto Base Station (FBS) adapts its pilot power, and thus the coverage, to the on-site traffic demand. Under low traffic conditions the FBSs, whose presence is not essential for the proper operation of the network, reside in a low power Listen Mode. In this way a relevant energy saving on entire femtocell network can be achieved. In a high-load scenario, FBSs dynamically create high capacity zones under interference constraints. This permits to improve system capacity and offload more traffic from the nearby macrocell and, in the same time, to minimize co-channel interference in the femtocell tier.

The concept of a densely deployed heterogeneous network is one of the main approaches of modern wireless networking research to satisfy the growth of the traffic demand. However, such trend leads to a significant network energy consumption increment. One of the effective techniques to save energy is to switch off some underutilized cells during off peak hours. In this line, the focus of this paper is to decide the number of base stations to switch off in order to maximize the energy saving, while maintaining coverage, capacity and Quality of Service. We use a combination of Grey Relational Analysis and Analytic Hierarchy Process tools to trigger the switch off actions, jointly considering multiple decision inputs for each cell. The co-tier interference, typical of small cell networks, is also considered in the decision making by introducing a graph-based technique for dynamic resource allocation.

In this paper, we present an improved selfconfiguration algorithm for LTE femtocells. In the absence of active users, femtocell resides in an energy saving state. As traffic demand becomes considerable, each Femto Base Station dynamically adapts its pilot power (and thus the coverage) to the on-site traffic demand. Our approach improves the overall system capacity and controls co-channel interference while enhancing Energy Efficiency of the overall cellular network. The proposed power control scheme is fully distributed and provides highly scalable, flexible and robust control without signaling overhead, that makes it suitable for a large-scale femtocell deployment.

The growth in mobile traffic demand is leading to a dense heterogeneous cellular network. This massive deployment of mobile equipment (i.e. base stations) may cause a high increment of the network energy consumption and therefore operational expenditure for operators. One of the most promising techniques to save energy (and costs) is to switch off some underutilized cells during off peak hours. In this line, our focus is to optimize the number of base stations in dense LTE pico cell deployments in order to maximize the energy saving, while satisfying the Quality of Service constraints. We use a combination of Fuzzy Logic, Grey Relational Analysis and Analytic Hierarchy Process tools to trigger the switch off actions, and jointly consider multiple decision inputs for each cell.