Abstract
Mobile network operators (MNOs) are deploying carrier-grade Wireless Local Area Network (WLAN) as an important complementary system to cellular networks. Access network selection (ANS) between cellular and WLAN is an essential component to improve network performance and user quality-of-service (QoS) via controlled loading of these systems. In emerging heterogeneous networks characterized by different cell sizes and diverse WLAN deployments, automatic tuning of the network selection functionality plays a crucial role. In this article, we present two distinct Self-Organizing Network (SON) schemes for tuning the ANS between the Long-Term Evolution (LTE) and WLAN systems. The SON functions differ in terms of availability of inter-system information exchange and internal algorithm design for traffic load control. System level simulations in a site-specific dense urban network show that the proposed schemes improve significantly the user quality of service (QoS), and network capacity over the reference scheme when offloading to WLAN is performed simply based on signal coverage.
Highlights
The explosive growth in data traffic [1, 2] and the limited availability of new licensed spectrum burden mobile network operators (MNOs) with great challenges to fulfill growing quality of service demands and increase competitiveness by reducing operational and capital expenditures (OPEX and CAPEX)
The resulting simulations below show that the adoption of Self-Organizing Network (SON) provides remarkable gains compared to the baseline scenario, which results in Wireless Local Area Network (WLAN) congestion
One can note that the percentage of user sessions on WLAN is quite similar regardless of the SON LC policy used. These results indicate that employing a more complex scheme with separate control over micro and macro user equipment (UE) steering to WLAN (‘Long-Term Evolution (LTE) LC’) brings slight performance improvements compared to the load control policy where only the micro cell load is used as input key performance indicator (KPI) (“Micro LC”)
Summary
The explosive growth in data traffic [1, 2] and the limited availability of new licensed spectrum burden mobile network operators (MNOs) with great challenges to fulfill growing quality of service demands and increase competitiveness by reducing operational and capital expenditures (OPEX and CAPEX). Most of the currently deployed network selection functions have severe limitations: they are either proprietary, autonomously controlled by the user’s device, or static and do not adapt to dynamically changing radio environments and radio access traffic load These approaches cannot optimally exploit HetNets’ potential in terms of optimal radio resource utilization and lead to suboptimal or degraded end user QoS. Any proposed SON algorithm yields to a more balanced loading across the layers/systems and improves the QoS of end users.All potential ANS solutions require, to a different extent, the exchange of information between systems and devices to assist the access selection decision.
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