Leveraging intelligence from network CDR data for interference aware energy consumption minimization

Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo

Disintegration and Coordination of Forecast Parameters of Socio-Economic Development and the Fuel and Energy Balance of the Region

The scope of strategic planning documents for the constituent entities of the Russian Federation, the procedure for their development and coordination on interregional and federal levels, the requirements for their content and conjunction with other long- and medium-term territorial programs are now approved by statute. The article presents the theoretical and methodological problems of detailing and interrelation of the region’s socio-economic development scenarios with the forecast parameters of regional energy consumption based on the fuel and energy balance under conditions of incomplete retrospective information. This situation is typical of the market environment, and some restrictions on access to statistical data are irremovable. This fact reduces the opportunity to apply formal and rigorous evaluation methods and the objectivity level of not only the forecast indicators, but also of the current ones. The coordination of these documents is methodologically and practically relevant due to the relative isolation of their formation process, a different level of detailing of the forecast scenarios, and a lack of the required information. The author uses the energy saving and energy efficiency measurement technique that is based on the structural comparison of performance, current and estimated fuel and energy balances, consistent with the region’s socio-economic development forecast. The author is also concerned with the development of this technique for the purpose of a comparative regional energy consumption analysis in retrospective and predictive periods. Since 2007, the author has been involved in practical calculations within the framework of the state order of the Ministry of Energy, Housing and Utilities of the Sverdlovsk Region. The article describes methodological characteristics of the author’s approaches to the development of variants of the fuel and energy balance, taking into account maintaining the official scenarios of socio-economic development of the region, the errors and the incompleteness of statistical data, and the regulatory requirements pertaining to the quality of forecasts