An Improved Handover Decision Algorithm for 5G Heterogeneous Networks

Heterogeneous Network (HetNet) appears as one of the most potential solutions for Fifth Generation (5G) mobile networks. It provides flexible and ubiquitous wireless connections to indoor and outdoor mobile users by deploying Smallcells underneath Macrocells. Hence, HetNet achieves higher throughput and better coverage. Besides, HetNet also supports the Internet of Things (IoT) technology and provides uninterrupted coverage to home appliances. However, frequent Handovers (HOs), Ping-Pong (PP) effects, and Load Balancing are the critical challenges of 5G HetNets due to the massive and unplanned deployment of Smallcells. Therefore, this paper proposes an optimized handover decision algorithm to improve the handover procedures and enhance the Quality of Service (QoS) in the 5G HetNets. This paper suggests a Machine Learning (ML) based technique that monitors the Reference Signal Received Power (RSRP), available radio resources, active time, and speed of User Equipment (UE) to ensure efficient HO decisions. Thus, the proposed algorithm reduces the frequent handovers and ping-pong effects by enhancing the HO procedures. By implementing a supervised ML approach, the algorithm achieves better results in terms of throughput and efficiency than the existing methods. In addition, the paper explains some challenges and research directions for researchers.