Ultra-Dense Networks (UDNs) were introduced to support high data rate services and improve the network capacity. The load across the small cells is unevenly distributed owing to random deployment of small cells, the mobility of user equipments (UEs) and the preference of small cells during the selection/reselection. The unbalanced load causes performance degradation in both the throughput and successful handovers. Moreover, it may be responsible for radio link failures as well. To address this problem, this paper proposes different proactive algorithms to balance the load across UDN small cells and compare them to previous reactive algorithms. Proactive algorithms distribute the UEs, one by one, to the access points (APs), while the reactive ones are only triggered when the load of the chosen small-cell cluster reaches a predefined threshold. The numerical analysis shows that the load distribution achieved by the proactive algorithm with user rejection is better than that in the reactive algorithms by 34.97%. In addition, the impact of the small-cell cluster layout on the load balancing results is also studied in this paper. The results indicate that the load distribution and the balance improvement ratio in the intersecting small-cell model outperform those in the sequential small-cell one by 48.98% and 22.43%, respectively.
- Intersecting small-cell model
- Proactive algorithm with rejection
- Proactive algorithm without rejection
- Reactive algorithms
- Sequential small-cell model