Resilience Study of Small Cell-Based Powering Deployment for Heterogeneous Networks
Hao Ran Chi, Ayman Radwan · 2023
Small cells have been proven to effectively serve the densification of users, which supports the framework of 5G. Therefore, small cells have drawn great research interest, targeting systemic optimization for their on-demand deployment to handle heterogeneous networks. On top of the previous research efforts, in this paper, we discuss the resilience of the on-demand small cell deployment to server ultra-dense heterogeneous networks, specifically focusing on powering strategies of small cells. Concretely, we formulate the optimization problem, jointly considering the achievable data rate, energy efficiency, and interference mitigation. Based on the formulation, we further propose the on-demand small cell powering strategy, which adopts the unsupervised learningbased algorithm, i.e., k-means clustering, as the backbone. Besides, the proposed powering strategy is further developed to enhance the resilience performance of the system, with the consideration of the situation of malfunctioned small cells. The simulation results show that the proposed system achieves 280 Mbps data rate and 7.58 MB/J, even under the scenarios with malfunctioned small cells, showcasing high resilience. Besides, such a Figure outperforms the selected two benchmarks, by {18.60%, 12.28% and {7.88% (resilience-related scenarios), 28.79%, respectively.