arXiv subjects

Neetu R R

Publications and source records attributed to Neetu R R.

2 recordsLinked to original sources

arXiv2025

Handover_Management_in_UAV_Networks_with_Blockages

We investigate the performance of unmanned aerial vehicle (UAV)-based networks in urban environments characterized by blockages, focusing on their capability to support the service demands of mobile users. The UAV-base stations (UAV-BSs) are modeled using a two-dimensional (2-D) marked- Poisson point process (MPPP), where the marks represent the altitude of each UAV-BS. Leveraging stochastic geometry, we analyze the impact of blockages on network reliability by studying the meta distribution (MD) of the signal-to-interference noise ratio (SINR) for a specific reliability threshold and the association probabilities for both line-of-sight (LoS) and non line-of-sight (NLoS) UAV-BSs. Furthermore, to enhance the performance of mobile users, we propose a novel cache-based handover management strategy that dynamically selects the cell search time and delays the received signal strength (RSS)-based base station (BS) associations. This strategy aims to minimize unnecessary handovers (HOs) experienced by users by leveraging caching capabilities at user equipment (UE), thus reducing latency, ensuring seamless connectivity, and maintaining the quality of service (QoS). This study provides valuable insights into optimizing UAV network deployments to support the stringent requirements in the network, ensuring reliable, low-latency, and high-throughput communication for next-generation smart cities.

eess.SP↗

arXiv2022

Cache Enabled UAV HetNets Access xHaul Coverage Analysis and Optimal Resource Partitioning

We study an urban wireless network in which cache-enabled UAV-Access points (UAV-APs) and UAV-Base stations (UAV-BSs) are deployed to provide higher throughput and ad-hoc coverage to users on the ground. The cache-enabled UAV-APs route the user data to the core network via either terrestrial base stations (TBSs) or backhaul-enabled UAV-BSs through an xHaul link. First, we derive the association probabilities in the access and xHaul links. Interestingly, we show that to maximize the line-of-sight (LoS) unmanned aerial vehicle (UAV) association, densifying the UAV deployment may not be beneficial after a threshold. Then, we obtain the signal to interference noise ratio (SINR) coverage probability of the typical user in the access link and the tagged UAV-AP in the xHaul link, respectively. The SINR coverage analysis is employed to characterize the successful content delivery probability by jointly considering the probability of successful access and xHaul transmissions and successful cache-hit probability. We numerically optimize the distribution of frequency resources between the access and the xHaul links to maximize the successful content delivery to the users. For a given storage capacity at the UAVs, our study prescribes the network operator optimal bandwidth partitioning factors and dimensioning rules concerning the deployment of the UAV-APs.

cs.IT↗