Energy efficiency as a SON mechanism for HSPA+ networks

The operation of mobile networks incurs significant amountsof energy consumption. From a network operation point of view reductionof energy consumption is not only a matter of environmental responsibilitybut also reduces the operational costs and improves network performanceminimizing some daily problems. In our study we apply an energy savingmechanism by means of Self-Organizing Networks (SON) functionality. Weshow that it is possible to reduce energy consumption and also control cellbreathing bringing more Quality of Service (QoS) to the network

Traffic-Driven Energy Efficient Operational Mechanisms in Cellular Access Networks

Recent explosive growth in mobile data traffic is increasing energy consumption in cellular networks at an incredible rate. Moreover, as a direct result of the conventional static network provisioning approach, a significant amount of electrical energy is being wasted in the existing networks. Therefore, in recent time, the issue of designing energy efficient cellular networks has drawn significant attention, which is also the foremost motivation behind this research. The proposed research is particularly focused on the design of self-organizing type traffic-sensitive dynamic network reconfiguring mechanisms for energy efficiency in cellular systems. Under the proposed techniques, radio access networks (RANs) are adaptively reconfigured using less equipment leading to reduced energy utilization. Several energy efficient cellular network frameworks by employing inter-base station (BS) cooperation in RANs are proposed. Under these frameworks, based on the instantaneous traffic demand, BSs are dynamically switched between active and sleep modes by redistributing traffic among them and thus, energy savings is achieved. The focus is then extended to exploiting the availability of multiple cellular networks for extracting energy savings through inter-RAN cooperation. Mathematical models for both of these single-RAN and multi-RAN cooperation mechanisms are also formulated. An alternative energy saving technique using dynamic sectorization (DS) under which some of the sectors in the underutilized BSs are turned into sleep mode is also proposed. Algorithms for both the distributed and the centralized implementations are developed. Finally, a two-dimensional energy efficient network provisioning mechanism is proposed by jointly applying both the DS and the dynamic BS switching. Extensive simulations are carried out, which demonstrate the capability of the proposed mechanisms in substantially enhancing the energy efficiency of cellular networks

Energy Efficient Resource and Topology Management for Heterogeneous Cellular Networks

This thesis investigates how resource and topology management techniques can be applied to achieve energy efficiency while maintaining acceptable quality of service (QoS) in heterogeneous cellular networks comprising high power macrocells and dense deployment of low power small cells. Partially centralised resource and topology management algorithms involving the sharing of decision making responsibilities regarding resource utilization and activation or deactivation of small cells among macrocells, small cells and a central node are developed. Resource management techniques are proposed to enable mobile users to be served by resources of a few small cells. A topology management scheme is applied to switch off idle small cells and switch on sleeping cells in accordance with traffic load and QoS. Resource management techniques, when combined with the topology management technique, achieve significant energy efficiency. A choice restriction technique that restricts users to resources from only a subset of suitable small cells is proposed to mitigate interference and improve QoS. A good balance between energy efficiency and QoS is achieved through this approach. Furthermore, energy saving under different generations of small cell base stations is investigated to provide insights to guide the design of energy saving strategies and the enhancement of existing ones. Also, an online, adaptive energy efficient joint resource and topology management technique is developed to correct deteriorating QoS conditions automatically by using a novel confidence level strategy to estimate QoS and regulate decision making epochs at the central node. Finally, a novel linear search scheme is applied together with database records of performance metrics to select appropriate resource and topology management policies for different traffic loads. This approach achieves better balance between QoS and energy efficiency than previous schemes proposed in the literature