Improving energy efficiency of communications systems using smart grids and heterogeneous powering

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The expansion in the telecommunication market has not led to only a shortage in spectrum but also to a huge**increase in energy consumption. As a result, the telecom market became one of the most power consumers and**carbon emitters. Researchers from the Centre for Energy-Efficient Telecommunications (CEET) and Bell Labs**[1] explain that the information communications and technology industry produces more than 830 million tons**of carbon dioxide (CO2), which is considered as the main Green House Gas (GHG), annually. Projections**suggest that this share is expected to double by 2020. That growth only represents the same carbon output as**4.9 million new cars on the road. This increase has led to a global awareness about the importance of**improving energy efficiency and necessity of relying on renewable energy sources for telecommunication**networks in order to limit GHG emissions. Although a massive research work has been done in the area of**energy management and usage of renewable sources in telecommunications, the existing research works suffer**from a lack of exploitation of the specific characteristics of the communication networks and the opportunities**resulting from the different degrees of freedom in these systems. Thus, innovative resource management**schemes need to be derived, where instead of focusing on the quantity of consumed energy; the economic and**environmental effects of this energy should be the main criteria of concern.**In this work, we aim to demonstrate how the integration of the energy utility functions in resource management**problems for communication systems could achieve significant improvements in terms of energy consumption**costs as well as GHG emissions. Thus, we propose to develop efficient resource allocation schemes for large**scale systems that seek optimizing environmental and economic energy usage as well as spectrum efficiency**while meeting the demand requirements. These results could be used for a-priori modelling and optimization**of communication systems powering architecture and to study their economic and environmental effects.