Matching with Externalities for Context-Aware User-Cell Association in Small Cell Networks

TL;DR

This paper introduces a context-aware user-cell association method for small cell networks that leverages device-specific information and application requirements to optimize network performance, demonstrating significant improvements over traditional approaches.

Contribution

It proposes a novel matching game framework incorporating device context and externalities, along with a distributed algorithm for stable, QoS-guaranteed cell associations.

Findings

Achieves up to 52% performance improvement over baseline methods.

Models the association problem as a many-to-one matching game with externalities.

Provides a distributed solution ensuring stable, QoS-aware user-cell matching.

Abstract

In this paper, we propose a novel user-cell association approach for wireless small cell networks that exploits previously unexplored context information extracted from users' devices, i.e., user equipments (UEs). Beyond characterizing precise quality of service (QoS) requirements that accurately reflect the UEs' application usage, our proposed cell association approach accounts for the devices' hardware type (e.g., smartphone, tablet, laptop). This approach has the practical benefit of enabling the small cells to make better informed cell association decisions that handle practical device-specific QoS characteristics. We formulate the problem as a matching game between small cell base stations (SBSs) and UEs. In this game, the SBSs and UEs rank one another based on well-designed utility functions that capture composite QoS requirements, extracted from the context features (i.e., application in use, hardware type). We show that the preferences used by the nodes to rank one another are interdependent and influenced by the existing network-wide matching. Due to this unique feature of the preferences, we show that the proposed game can be classified as a many-to-one matching game with externalities. To solve this game, we propose a distributed algorithm that enables the players (i.e., UEs and SBSs) to self-organize into a stable matching that guarantees the required applications' QoS. Simulation results show that the proposed context-aware cell association scheme yields significant gains, reaching up to 52% improvement compared to baseline context-unaware approaches.