A context-aware matching game for user association in wireless small cell networks

TL;DR

This paper introduces a context-aware user association method for small cell networks that uses user velocity and trajectory information to improve traffic balancing and QoS satisfaction, outperforming traditional approaches.

Contribution

It presents a novel matching theory-based algorithm that incorporates user context for stable user-cell associations in small cell networks.

Findings

Improved traffic balancing among small cells.

Enhanced user QoS satisfaction.

Significant performance gains over traditional methods.

Abstract

Small cell networks are seen as a promising technology for boosting the performance of future wireless networks. In this paper, we propose a novel context-aware user-cell association approach for small cell networks that exploits the information about the velocity and trajectory of the users while also taking into account their quality of service (QoS) requirements. We formulate the problem in the framework of matching theory with externalities in which the agents, namely users and small cell base stations (SCBSs), have strict interdependent preferences over the members of the opposite set. To solve the problem, we propose a novel algorithm that leads to a stable matching among the users and SCBSs. We show that the proposed approach can better balance the traffic among the cells while also satisfying the QoS of the users. Simulation results show that the proposed matching algorithm yields significant performance advantages relative to traditional context-unaware approaches.