Location Assisted Handover Optimization for Heterogeneous Wireless Networks

Mobile users typically experience better connectivity if their mobile device performs handover to an available WiFi network rather than using a cellular network. For a moving user the window of opportunity is limited and the timing of the handover is therefore crucial. In this work we propose two location-based look-ahead handover prediction algorithms that are based on the assumption that a database of expected throughput for a given location of all networks is available. The first algorithm uses an analytical formulation of the handover problem to determine the optimal sequence of handovers within a time window, which is computationally feasible for up to 3-4 handovers within the window. The second algorithm is a heuristic algorithm, which is computationally feasible for any reasonable number of handovers within the window. We have used simulations to obtain the achieved throughput of these algorithms for a mobile user in an urban scenario with ubiquitous cellular coverage and 250 WiFi APs/km, and compared the results to a hysteresis-based greedy algorithm and the case of ”always cellular-connected”. Our results show that the proposed look-ahead algorithms outperform the hysteresis-based and ”always cellular-connected”, but also show that the look-ahead algorithms are highly dependent on accurate movement tracking and movement prediction systems. The heuristic algorithm is also shown to achieve the highest throughput for large look-ahead windows.