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Title: Features detection based blind handover using kullback leibler distance for 5G hetnets systems
Authors: Hayar, Aawatif
Keywords: Akaike information criterion
Akaike weight
Kullback leibler distance
Small cells
Issue Date: Jun-2020
Publisher: IAES International Journal of Artificial Intelligence
Abstract: The Fifth Generation of Mobile Networks (5G) is changing the cellular network infrastructure paradigm, and small cells are a key piece of this shift. But the high number of small cells and their low coverage involve more Handovers to provide continuous connectivity, and the selection, quickly and at low energy cost, of the appropriate one in the vicinity of thousands is also a key problem. In this paper, we propose a new method, to have an efficient, blind and rapid handover just by analysing received signal probability density function instead of demodulating and analysing received signal itself as in classical handover. The proposed method exploits kullback leibler distance (KLD), akaike information criterion (AIC) and akaike weights, in order to decide blindly the best handover and the best base station (BS) for each user.
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