Heterogeneous networks (HetNets) can increase network capacity through complementing the macro-base-station with low-power nodes, in response to the ongoing exponential growth in data traffic demand. While, unprecedented challenges exist in the planning, optimization, and maintenance in HetNets, especially activities such as cell outage detection and mitigation are labor-intensive and costly. One potential solution to address these issues is to introduce the extensively attracted self-organizing network (SON). This paper is mainly devoted to cell outage detection and compensation methods in two-tier HetNets where macrocell and picocells are coexisted. AK-nearest neighbor (KNN) classification algorithm is employed to detect the cell outage automatically. Consider the breakdown picocell can reload its degraded service to the overlapped macrocell via vertical handover; only the breakdown macrocell executes the performance compensation. Power adjustment on each resource block is carried out via Lagrange optimizing algorithm to compensate the breakdown cell. Through intensive numerical experiments, with the help of our proposal, the outage cells can be successfully detected and performance gain for the outage macrocell can reach 91.4% withα=1/3.
Prototyping of LAI and FPAR Retrievals from GOES-16 Advanced Baseline Imager Data Using Global Optimizing Algorithm
