Selection of UE-based Virtual Small Cell Base Stations using Affinity Propagation Clustering

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Abstract
5G will require a number of Key Technological Components to meet its very ambitious goals, including Heterogeneous Networks a nd Small Cells. The Dense Deployme nt of Small Cell Base Stations (SBSs) will play a major role as they can be installed in a more targeted manner to relieve traffic in hot spot areas, increase coverage, and spectral efficiency. However, the current deployment of the SBS is static (examples include Femto, Pico, and Nano cells), normally deployed on demand around hotspots. In the scenario of unpredictable crowd movement, these static deployment of small cell can be inefficient with high CAPEX and OPEX. This paper focuses on the scenario where UE-based Virtual Small Cell Base Stations (UE-VBSs) can be dynamically selected among UEs to deal effectively with the non-stationary, non-uniform distribution of mobile traffic with respect to time and space domain. To implement this concept, we propose an efficient clustering technique (Affinity Propagation Clustering) to select the best set of UE-VBSs to supplement an overlay loaded SBS. Simulative evaluation highlights salient features of the technique, as well as its limitations with regard to scalability. Further, we discuss the modification of the algorithm according to our objec tive sc enario focusing on red ucing the message passing procedure to and from only a number of eligible UE-VBSs using the power received by a UE from the eligible UE-VBSs as a parameter. The algorithm is implemented and evaluated in MATLAB and, also validated using NS3 simulator.

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