Dynamic clustering and user association in wireless small-cell networks with social considerations

Abstract

<div lang="en" class="abs"><p class="abs_header">Abstract</p><p>In this paper, a novel social network-aware user association in wireless small cell networks with underlaid deviceto-device (D2D) communication is investigated. The proposed approach exploits strategic social relationships between user equipments (TIEs) and their physical proximity to optimize the overall network performance. This problem is formulated as a matching game between TIEs and their serving nodes (SNs) in which, an SN can be a small cell base station (SCBS) or an important UE with D2D capabilities. The problem is cast as a many-to-one matching game in which TIEs and SNs rank one another using preference relations that capture both the wireless aspects (i.e., received signal strength, traffic load, etc.) and users’ social ties (e.g., TIE proximity and social distance). Due to the combinatorial nature of the network-wide TIE-SN matching, the problem is decomposed into a dynamic clustering problem in which SCBSs are grouped into disjoint clusters based on mutual interference. Subsequently, an TIE-SN matching game is carried out per cluster. The game under consideration is shown to belong to a class of matching games with externalities arising from interference and peer effects due to users social distance, enabling TIEs and SNs to interact with one another until reaching a stable matching. Simulation results show that the proposed social-aware user association approach yields significant performance gains, reaching up to 26%, 24%, and 31% for 5th, 50th, and 95th percentiles for TIE throughputs, respectively, as compared to the classical social-unaware baseline.</p></div>