Energy Saving in Heterogeneous Cellular Networks with User Classification

Leveraging massive databases about mobile user activities, one way is to exploit information about user profiles (e.g. rate requirements, traffic type, etc) and allocate resources according to their needs. To study this, in this paper, users are assumed to belong to two communities which differ in their rate requirement in heterogeneous network setting. Both Base Station (BS) and users are modeled according to independent homogeneous Poisson Point Processes (Poisson Point Process (PPP)). To demonstrate the advantage of user classification, two sleeping strategies for Small Cell (SC) are investigated to improve energy efficiency. It is shown that using rate-based user classification in devising sleeping strategies provides better energy consumption and fair resource allocation compared to obliviously allocating maximum rate for all the users.