Resource Allocation for Cellular/WLAN Integrated Networks

Abstract

The next-generation wireless communications have been envisioned to be supported by heterogeneous networks using various wireless access technologies. The popular cellular networks and wireless local area networks (WLANs) present perfectly complementary characteristics in terms of service capacity, mobility support, and quality-of-service (QoS) provisioning. The cellular/WLAN interworking is thus an effective way to promote the evolution of wireless networks. As an essential aspect of the interworking, resource allocation is vital for efficient utilization of the overall resources.

Specially, multi-service provisioning can be enhanced with cellular/WLAN interworking by taking advantage of the complementary network strength and an overlay structure. Call assignment/reassignment strategies and admission control policies are effective resource allocation mechanisms for the cellular/WLAN integrated network. Initially, the incoming calls are distributed to the overlay cell or WLAN according to call assignment strategies, which are enhanced with admission control policies in the target network. Further, call reassignment can be enabled to dynamically transfer the traffic load between the overlay cell and WLAN via vertical handoff. By these means, the multi-service traffic load can be properly shared between the interworked systems.

In this thesis, we investigate the load sharing problem for this heterogeneous wireless overlay network. Three load sharing schemes with different call assignment/reassignment strategies and admission control policies are proposed and analyzed. Effective analytical models are developed to evaluate the QoS performance and determine the call admission and assignment parameters. First, an admission control scheme with service-differentiated call assignment is studied to gain insights on the effects of load sharing on interworking effectiveness. Then, the admission scheme is extended by using randomized call assignment to enable distributed implementation. Also, we analyze the impact of user mobility and data traffic variability. Further, an enhanced call assignment strategy is developed to exploit the heavy-tailedness of data call size. Last, the study is extended to a multi-service scenario. The overall resource utilization and QoS satisfaction are improved substantially by taking into account the multi-service traffic characteristics, such as the delay-sensitivity of voice traffic, elasticity and heavy-tailedness of data traffic, and rate-adaptiveness of video streaming traffic.