Scalability study of backhaul capacity sensitive network selection scheme in LTE-wifi HetNet

Ting, Alvin and Chieng, David and Kwong, Kae Hsiang and Andonovic, Ivan and Wong, K. D. (2016) Scalability study of backhaul capacity sensitive network selection scheme in LTE-wifi HetNet. Transactions on Emerging Telecommunications Technologies. ISSN 2161-3915 (https://doi.org/10.1002/ett.3013)

[thumbnail of Ting-etal-TETT-2015-Scalability-study-of-backhaul-capacity-sensitive-network-selection-scheme]
Preview
Text. Filename: Ting_etal_TETT_2015_Scalability_study_of_backhaul_capacity_sensitive_network_selection_scheme.pdf
Accepted Author Manuscript

Download (3MB)| Preview

Abstract

Wireless Heterogeneous Network (HetNet) with small cells presents a new backhauling challenge which differs from those of experienced by conventional macro-cells. In practice, the choice of backhaul technology for these small cells whether fiber, xDSL, point–to-point and point-to-multipoint wireless, or multi-hop/mesh networks, is often governed by availability and cost, and not by required capacity. Therefore, the resulting backhaul capacity of the small cells in HetNet is likely to be non-uniform due to the mixture of backhaul technologies adopted. In such an environment, a question then arises whether a network selection strategy that considers the small cells’ backhaul capacity will improve the end users’ usage experience. In this paper, a novel Dynamic Backhaul Capacity Sensitive (DyBaCS) network selection schemes (NSS) is proposed and compared with two commonly used network NSSs, namely WiFi First (WF) and Physical Data Rate (PDR) in an LTE-WiFi HetNet environment. The proposed scheme is evaluated in terms of average connection or user throughput1and fairness among users. The effects of varying WiFi backhaul capacity (uniform and non-uniform distribution), WiFi-LTE coverage ratio, user density and WiFi access points (APs) density within the HetNet form the focus of this paper. Results show that the DyBaCS scheme generally provides superior fairness and user throughput performance across the range of backhaul capacity considered. Besides, DyBaCS is able to scale much better than WF and PDR across different user and WiFi densities.