HyPE: Online Hybrid Pseudo-Bayesian Estimation Method for S-ALOHA-Based Tactical FANETs

J Jeon, J Lee, T Kim, J Ahn, Y You, M Lee, H Yu… - IEEE …, 2024 - ieeexplore.ieee.org
Significant challenges are involved in tactical flying ad-hoc network (FANET) missions
because network environments are very dynamic. In addition, energy-efficient network …

Wireless Adaptive Framed Pseudo-Bayesian Aloha (AFPBA) Algorithm with Priorities

MH Habaebi, BM Ali, MR Mukerjee - International Journal of Wireless …, 2001 - Springer
In this paper, we propose a new priority algorithm to control the access to the wireless ATM
MAC uplink frame, for multimedia traffic like wireless ATM, similar to the Pseudo-Bayesian …

[PDF][PDF] A Fast Adaptive Control Algorithm for Slotted ALOHA.

F Fang, M Jiang - J. Commun., 2016 - jocm.us
The control algorithm which is in order to achieve the aim of keeping throughput stability is
needed in the Slotted ALOHA (S-ALOHA) protocol. The core of the control algorithm is to …

Revisiting slotted ALOHA: density adaptation in FANETs

A Eroğlu, E Onur - Wireless Personal Communications, 2022 - Springer
Unmanned aerial vehicles have been widely used in many areas of life. They communicate
with each other or infrastructure to provide ubiquitous coverage or assist cellular and sensor …

The ergodic rate density of ALOHA wireless ad-hoc networks

Y George, I Bergel, E Zehavi - IEEE Transactions on Wireless …, 2013 - ieeexplore.ieee.org
In recent years, much attention has been paid to the analysis of random wireless ad hoc
networks (WANETs) that combine the effect of the physical layer and the medium access …

Smart unmanned aerial vehicles as base stations placement to improve the mobile network operations

Z Zhao, P Cumino, C Esposito, M Xiao… - Computer …, 2022 - Elsevier
Future mobile communication networks need Unmanned Aerial Vehicles as Base Stations
(UAVasBSs) with the fast-moving and long-term hovering capabilities to guarantee …

Machine learning for predictive deployment of UAVs with multiple access

L Lu, Z Yang, M Chen, Z Zang… - arXiv preprint arXiv …, 2020 - arxiv.org
In this paper, a machine learning based deployment framework of unmanned aerial vehicles
(UAVs) is studied. In the considered model, UAVs are deployed as flying base stations (BS) …

Modeling and online adaptation of ALOHA for low-power wide-area networks (LPWANs)

JB Seo, BC Jung, H Jin - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Unslotted ALOHA protocol has been adopted as a channel access mechanism in
commercial low-power wide-area networks (LPWANs), such as Sigfox and long-range …

Gaussian approximations for the probability mass function of the access delay for different backoff policies in S-ALOHA

ME Rivero-Angeles, D Lara-Rodriguez… - IEEE …, 2006 - ieeexplore.ieee.org
In this letter, closed-form non-recursive expressions for the probability mass function (pmf) of
the access delay are addressed. As the exact non-recursive expression for the pmf of the …

Optimal Tethered-UAV Deployment in A2G Communication Networks: Multi-Agent Q-Learning Approach

S Lim, H Yu, H Lee - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
An unmanned aerial vehicle-mounted base station (UAV-BS) is a promising technology for
the forthcoming sixth-generation wireless networks, owing to its flexibility and cost …