Load Balancing of Elastic Data Traffic in Heterogeneous Wireless Networks

The increasing amount of mobile data traffic has resulted in an architectural innovation in cellular networks through the introduction of heterogeneous networks. In heterogeneous networks, the deployment of macrocells is accompanied by the use of low power pico and femtocells (referred to as microcells) in hot spot areas inside the macrocell which increase the data rate per unit area. The purpose of this thesis is to study the load balancing problem of elastic data traffic in heterogeneous wireless networks. These networks consist of different types of cells with different characteristics. Individual cells are modelled as an M/G/1 - PS queueing system. This results in a multi-server queueing model consisting of a single macrocell with multiple microcells within the area. Both static and dynamic load balancing schemes are developed to balance the data flows between the macrocell and microcells so that the mean flow-level delay is minimized. Both analytical and numerical methods are used for static policies. For dynamic policies, the performance is evaluated by simulations. The results of the study indicate that all dynamic policies can significantly improve the flow-level delay performance in the system under consideration compared to the optimal static policy. The results also indicate that MJSQ and MP are best policies although MJSQ needs less state information. The performance gain of most of the dynamic polices is insensitive with respect to the flow size distribution. In addition, many interesting tests are conducted such as the effect of increasing the number of microcells and the impact of service rate difference between macrocell and microcells