Energy efficiency of 3G/4G mobile networks

OData support
Supervisor:
Dr. Simon Vilmos
Department of Networked Systems and Services

The world of mobile networks is probably one of the fastest growing information technology sector. High pace of development of mobile phones has urged the development of newer and newer software solutions for faster network connection and data transfer. The new phone users came up with higher demand for applications, which significantly increased the demand for data speeds. Previous technologies were not able to serve the growing needs of consumers, so there was a necessity for new transmission technology solutions, which included all the communication layer reconsideration. The rapid progress has been made in this area, as a result a number of new technical solutions has met the demands of the users. In fact, there functioned simpler user devices, which were left out of the new solutions. The previous systems continued using the existing infrastructure, which has led to a kind of overlay system. This multiple overlapping resulted into increased consumption of energy and natural resources (ether) pollution. In order to preserve the Earth's energy resources my work is aimed to develop a solution that may reduce power consumption and does not require serious interference into network infrastructure.

The following thesis is basically divided into two parts. One of the results of the BUTE Department Networked Systems and Services research colleagues is used to describe the algorithmic approach that I have developed to optimize the amount of consumption. Then I am explaining why I have chosen this algorithmic approach to achieve my objective, describing in detail the operating principle of the algorithm and technical implementation of my program.

The second part contains a detailed description of my simulation system which allows me to test the algorithm I have developed. The simulation works on real maps and calculates the energy consumption of the stations which it depends upon: frequency, traffic volume, landscape, etc. Applying this algorithmic optimization, I was able to switch on and switch off some part of base mobile station supporting different QoS, as well as granting full availability for all users. To summarize, I have outlined the process of simulation and analyzed the results achieved.

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