Mobility load balancing in self-organizing OFDMA networks

In any cellular network, load imbalance results in ine cient resource utilization and low throughput for cell-edge users. Mobility Load Balancing (MLB) is an essential feature of self-organizing networks (SON) concept in long term-evolution (LTE) and introduced as a tool to balance the uneven cell load among the cells. MLB functionality changes the virtual cell borders with automatic handover parameter adjustment so that some of the load of the overloaded cells can be shifted to the less loaded neighbors. One other major problem for cell-edge users is inter-cell interference (ICI). To mitigate the ICI problem various frequency planning schemes are proposed in the scope of intercell interference coordination (ICIC). A signi cant number of studies have investigated MLB however previous solutions are isolated from ICI mitigation techniques and executed for a speci c scheduling strategy. In this thesis, the performance of MLB is considered jointly with static ICIC approaches for di erent scheduling strategies. We evaluate the performance of MLB for di erent frequency planning schemes, i.e. strict fractional frequency reuse (FFR) and soft frequency reuse (SFR) using di erent resource scheduling strategies, i.e. round-robin, proportional fair and best-CQI. We also apply reuse-1 and reuse-3 methods to provide benchmarks while showing the gain of ICI mitigation. In the cases of FFR and SFR, the intra-cell LB mechanism is included in MLB functionality together with inter-cell MLB. Results show that static ICIC enhances MLB performance in terms of cell-edge spectral e ciency and reduces the number of unsatis ed users. Additionally, we observe the performance improvement when the non-adjacent neighbors of the overloaded cell are included in the optimization area.