A Delay-Aware Approach for Energy Efficient Handover Procedure in Millimeter wave Heterogeneous Network
Abstract
This paper presents a delay-aware approach for energy efficient handover procedure in millimeter-Wave (mmWave) Heterogeneous Network (HetNet). In large open dense areas, high numbers of people use their smart phones to share pictures or data and download other information. This behavior creates traffic profiles that differ from those typically seen in the traditional network in less dense areas where less uplink traffic and less frequent packet transmission will be experienced. The mm-Wave HetNet deployment is a promising solution to address the spectrum shortage in 5G cellular systems. This is due to its large bandwidth available for meeting the increasing demand of mobile traffic. However, a major challenge for mm-Wave HetNet is to manage the user mobility and handovers in mm-Wave small cells. In addressing this problem, researchers are currently focused on applying several cell selections approaches in improving on the handover process for user’s mobility. Despite a number of efforts made to mitigate this problem, network users still experience significant degradation in call quality owing to the dissimilarities in access technologies available and the user unpredictable movement patterns in both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) paths. This paper proposes a handover decision algorithm, which is based on the user’s changing speed, a normalized transmit power of the Base Stations (BS) and network connection time in order to make the handover decision better whilst guaranteeing improved system throughput. Results obtained using MATLAB R2020b version showed that the developed handover algorithm (EE-VHDA) reduced the number of handovers with respect to the number of Femto Base Stations (FBSs) by 52.83% and 8% when compared with the existing RBH and SMART algorithms respectively. Additionally, the developed algorithm obtained 2.74% and 5.64% improvement in system throughput with respect to the number of FBSs in comparison to the existing RBH and SMART algorithms respectively.
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