Heuristic approach for jointly optimising FeICIC and UAV locations in multi‐tier LTE‐advanced public safety HetNet

Abstract

Unmanned aerial vehicles (UAVs) enabled networks can enhance wireless connectivity and support emerging services. However, this would require system-level understanding to modify and extend the existing terrestrial network infrastructure. In this study, the authors integrated UAVs as user equipment and base stations into an existing long term evolution (LTE)-Advanced heterogeneous network (HetNet) and provide system-level insights of this three-tier LTE-Advanced air-ground HetNet (AG-HetNet). The performance of AG-HetNet was evaluated through brute-force technique and heuristics algorithms in terms of the fifth percentile spectral efficiency (5pSE) and coverage probability. In particular, system-wide 5pSE and coverage probability were compared, when unmanned aerial base stations (UABSs) are deployed on a fixed hexagonal grid and when their locations are optimised using a genetic algorithm (GA) and elitist harmony search algorithm based on the genetic algorithm (eHSGA); while jointly optimising the inter-cell interference coordination (ICIC) and cell range expansion (CRE) network parameters for different ICIC techniques. The simulation results show that the heuristic algorithms (GA and eHSGA) outperform the brute-force technique and achieve better peak values of coverage probability and 5pSE. Simulation results also show that a trade-off exists between peak values and computation time when using heuristic algorithms. Furthermore, the three-tier hierarchical structuring of reduced power subframes further-enhanced ICIC (FeICIC) defined in 3GPP Rel-11 provides considerably better 5pSE and coverage probability than the 3GPP Rel-10 with almost blank subframes eICIC. They also investigated the network performance for different practical deployment heights of UABS and they found low-altitude UABSs to perform sparsely better than medium-altitude UABSs.