Ultra-Dense Networks (UDNs) can be used to improve coverage. With limited network capacity and the dense development of wireless networks, heterogeneous ultra-dense networks are set to satisfy the increasing demands of mobile users. However, the dense deployment of small cells in the hotspots of UDN networks generates an uneven traffic distribution. To address this problem, this paper proposes novel load balancing approaches implemented within the small cells, which are formed based on the Radio-over-Fiber (RoF) system. To select the best overlapping zone and then the best candidate user to be handed-over between the access points of the small cells, a common zone approach, a worst zone approach and a mixed approach are suggested. The results indicate that the proposed algorithm improves the performance of UDN networks when the load is unbalanced. The balance improvement ratio can reach on average 89.16%.

Several solutions tackling hybrid systems of wireless access networks including WLAN (Wifi: Wireless Fidelity) and 2nd and 3rd generations of Mobile Networks (GSM/GPRS-UMTS) have already been deployed. These first solutions based on the concept of Generic Access Networks (formerly known as UMA (Unlicensed Mobile Access)) are mainly ad-hoc solutions which have to be instantiated for each kind of access networks. The IEEE 802.21 group proposed a more generic solution for this integration covering the 4th generation of wireless networks: the MIH reference model. Several mechanisms were proposed for terrestrial networks. In this paper, we intend to extend those solutions to a satellite system based on the DVB-S/RCS protocol stack. We shown that a possible evolution of the Media Independent Handover (MIH) reference model, taking into account DVB-RCS (Digital Video Broadcasting Return Channel via Satellite) satellite system, could be implemented to integrate a Wireless terrestrial network (based on WiMAX for instance) and a satellite system.

As one of the main technologies in 5G networks, Ultra-dense networks (UDNs) can be used to improve the network coverage. The dense deployment of small cells in UDN hotspots generates an uneven traffic distribution. In this paper, we propose a novel mechanism in order to transfer the extra users from the small cells to the macrocells based on several load balancing approaches implemented within the small cells, which are formed based on the Radio-over-Fiber (RoF) system. To select the best overlapping zone and then the best candidate user to be handed-over between the access points of the small cells, a common zone approach, a worst zone approach and a mixed approach are proposed. With the objective of transferring the extra users to the macrocells, we suggest a transfer after approach, a transfer before approach and an active approach. The simulation results indicate that the proposed approaches succeed to balance the load among the access points and to migrate the required load from the overloaded small cells to the macrocells in selective way. In some cases, the balance improvement ratio can reach 97.94%. Moreover, the overall balance efficiency is increased by 51.32% compared to the case without transferring users to the macrocells. CCS Concepts• Network ➝Network Performance evaluation ➝Network performance analysis. Keywords UDN, RoF, load balancing algorithm, common zone approach, worst zone approach, mixed approach, transfer after approach, transfer before approach, active approach.

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In Ultra-Dense Networks (UDNs), the load across the small cells is not equally distributed due to the random deployment of small cells, the mobility of user equipments (UEs) and the preference of small cells during the selection and reselection. This results in performance degradation concerning the throughput and successful handovers. To address this problem, this paper proposes proactive algorithms for balancing the load across the small-cell clusters and compares their balancing results to the previous reactive algorithms. The proactive algorithms distribute the new UEs, one by one, to the small cells, while the reactive algorithms are only triggered when the load of the chosen cluster reaches a predefined threshold. In addition, this paper employs the design structure matrix (DSM) method in order to balance the load across the small cells and to reduce the inter-communications between the access points (APs) as well. The numerical analysis indicates that the load distribution and the balance efficiency using the proactive algorithm with user rejection are better than those in the reactive algorithms by 34.97% and 9.09%, respectively. Moreover, the proactive algorithm without user rejection with the DSM method achieves the best balance efficiency and reduces the inter-communications between the APs in some cases by 60.60%.