Energy Consumption Tradeoffs In Heterogeneous Networks

With the development of human society and technology, communication technologies are going through a prosperous development process, and various kinds of radio access technologies have come into being. For example, in future communication networks, the5G/WLAN/WiMax would coexist and consist a multi-RAT(multiple Radio Access Technology) heterogenous network. In each layer of RAT, there would be multiple sub-layers. For example, in the5G single-RAT(single Radio Access Technology) heterogeneous network, there would be underlaying macro cells and small cells. The main topic of this article is to explore the energy efficiency tradeoffs in these heterogeneous networks.Small cell underlaying single-RAT heterogenous network is one of the key technologies of5G communications. Since most of the traffic load is generated in indoor environment, the small cell technology proposed by3GPP is becoming one of the most promising key techniques of future wireless communication system. The implementation of small cell network could not only increase the indoor coverage but also enhance the quality of experience of the mobile users on the cell edge. Furthermore, through spectrum reusing, small cell networks are able to bring spectrum efficiency increase. Besides, the energy consumption of user terminals are reduced, resulting from the shortened transmission distances and improved channel states. Nevertheless, the wide spread of small cell network could cause a huge network energy consumption increase, thus the energy efficient small cell network has been a hot research topic in both academia and industry. We pay our attention on the energy consumption tradeoff between user and small cell network. The introduce of sleep technique of small cells effectively cuts off the network energy consumption and reduces cross-tier and co-tier interference. During periods when the network is in low load, the dynamic shutdown of small cells could save network energy. However, when a small cell enters sleep mode, the user terminals in its coverage are forced to access the macro base station. Although small network energy consumption is reduced, the energy consumption of user terminals would rise due to increase of transmission distances. Thus, in this paper, we mainly study the energy consumption tradeoffs between user and small cell network. The target is to optimize the weighted sum of energy consumption of user equipment and small cell network through small cell sleep control, and study the energy consumption tradeoff relationships in single cell network where small cells are randomly distributed. The research result provides a valuable reference to the network operators to balance network energy consumption reduction and the quality of experience. Through properly selecting the weight factors and sleep control mechanism, the overall system energy consumption could be reduced and user experience could be balanced.Multi-RAT heterogeneous network is the general tendency of future communication networks with the advantages of low interference, high spectrum efficiency and large throughput. In multi-RAT heterogenous network, spectrum resources were orthogonally allocated among different RAT, so that the interference is mitigated. Moreover, users could simultaneously access to different layers of RAT, which brings multiplexing gain and throughput enhancement. Last but not least, system spectrum efficiency would be increased through fractional spectrum reuse among different RAT. In this paper, we focus on the uplink energy efficiency of users in multi-RAT heterogenous network. The energy efficiency enhances the user experience through extending the battery life of mobile terminals. We set the uplink energy efficiency of single user as the optimization objective, and formulates a multiple objective optimization problem to study the relationships of each user’s uplink energy efficiency.Our research gives an insight of the uplink energy efficiency tradeoff among users in multi-RAT heterogeneous network. A joint spectrum and power allocation scheme is put forward to achieve the Pareto optimal energy efficiency of users under a certain set of weight factors with the QoS constraints.