Analytical Modeling and Performance Evaluation of Cell Selection Algorithms for Mobile Networks with Backhaul Capacity Constraints

Mobile backhaul has moved to the forefront of wireless industry hot topics. The progressive deployment of spectrally efficient radio access technologies (e.g. HSPA, LTE, WiMAX) in mobile broadband is turning into stringent capacity requirements on the backhaul network. This makes backhaul capacity to become a potential network bottleneck in some deployment scenarios. While more cost-efficient transmission technologies are needed to increase the capacity of mobile backhaul, optimization solutions to get the most out of the backhaul capacity are also necessary. This paper analyses the possibility to exploit load balancing among base stations to improve backhaul capacity utilization. Load balancing is realized through cell selection algorithms accounting for both radio interface and backhaul conditions. An analytical model aimed at evaluating the performance of cell selection strategies for mobile networks with backhaul capacity constraints is developed. The analytical model is used to evaluate the performance of a novel backhaul-aware cell selection algorithm and compare it with classical schemes based exclusively on radio information. Obtained results show that the proposed algorithm can achieve a utilization of backhaul resources higher than the traditional cell selection schemes while providing the same radio interface performance. Analytical results have been verified by means of simulation.