Optimizing Cell Association and Stability in Integrated Aerial-to-Ground Next-Generation Consumer Wireless Networks

Unmanned aerial vehicles (UAVs) offer advantages in serving as aerial small cells (ASCs) to support public safety terrestrial cells (PSTCs) while providing pervasive coverage during disasters. To ensure reliable communications for long-term evolution-based public safety (PS-LTE) users, it is crucial to obtain an accurate understanding of network performance for practical cell association design and network stability. This comprehension is vital for the practical design of cell associations and for maintaining network stability in next-generation consumer wireless networks. For this purpose, we first employ a flexible biased cell association (FBCA) policy that optimally selects the bias factor where a PS-LTE user (PUE) connects to the eNodeB (eNB) giving the maximum power for the received signal. Then, we present a resource allocation and subframe–type selection by formulating stochastic optimization programming to resolve system stability issues in the coexisting PS-LTE and LTE-based high-speed railway (LTE-R) networks and PS-LTE and UAV networks. In addition to this, we employ the Lyapunov optimization technique to seek an optimal almost blank subframe (ABS) algorithm with dynamic delay-aware resource allocation (ADDRA) to resolve the problem of network stability. Using ADDRA, the PS-LTE eNodeB (PSeNB), the aerial eNodeBs (AeNBs), and the LTE-R eNodeBs (ReNBs) obtain up-to-date queues of attached users and accordingly compute a matrix for scheduling resources based on channel state information (CSI) feedback. The simulation results of the UAV-assisted networks using FBCA and ADDRA in coexisting PS-LTE/LTE-R and PS-LTE/UAV networks demonstrate a significant improvement when compared with other state-of-the-art techniques.