Energy Saving in Heterogeneous Cellular Networks with User Classification


S. Sadananda, A. Behboodi, R. Mathar,


        Having massive databases about mobile user activities, cellular network operators can employ data analytics to extract information about user profiles (e.g. rate requirements, traffic type, etc) and provide awareness for better adaption of network parameters and resources. In this paper, it is investigated how simple data-driven information about users can improve performance of cellular networks with focus on energy efficiency. Users are assumed to belong to two classes differing in their rate requirements in heterogeneous network setting. Both Base Station (BS) and users are modeled according to independent homogeneous Poisson Point Process (PPP). Two sleeping strategies are considered for Small Cell (SC) namely random and strategic sleeping. Using stochastic geometry framework, it is shown that using rate-based user classification in devising sleeping strategies provides better energy consumption and fair resource allocation compared to oblivious resource allocation for all the users.

BibTEX Reference Entry 

	author = {Sudarshan Sadananda and Arash Behboodi and Rudolf Mathar},
	title = "Energy Saving in Heterogeneous Cellular Networks with User Classification",
	booktitle = "21st International ITG Workshop on Smart Antennas",
	address = {Berlin, Germany},
	month = Mar,
	year = 2017,
	hsb = RWTH-CONV-220339,


 Download paper  Download bibtex-file

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights there in are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.