@Article{cmes.2023.030872,
AUTHOR = {Baofeng Ji, Ying Wang, Weixing Wang, Shahid Mumtaz, Charalampos Tsimenidis},
TITLE = {Outage Analysis of Optimal UAV Cooperation with IRS via Energy Harvesting Enhancement Assisted Computational Offloading},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {138},
YEAR = {2024},
NUMBER = {2},
PAGES = {1885--1905},
URL = {http://www.techscience.com/CMES/v138n2/54622},
ISSN = {1526-1506},
ABSTRACT = {The utilization of mobile edge computing (MEC) for unmanned aerial vehicle (UAV) communication presents a viable solution for achieving high reliability and low latency communication. This study explores the potential of employing intelligent reflective surfaces (IRS) and UAVs as relay nodes to efficiently offload user computing tasks to the MEC server system model. Specifically, the user node accesses the primary user spectrum, while adhering to the constraint of satisfying the primary user peak interference power. Furthermore, the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes, namely time switching (TS) and power splitting (PS). The selection of the optimal UAV is based on the maximization of the instantaneous signal-to-noise ratio. Subsequently, the analytical expression for the outage probability of the system in Rayleigh channels is derived and analyzed. The study investigates the impact of various system parameters, including the number of UAVs, peak interference power, TS, and PS factors, on the system’s outage performance through simulation. The proposed system is also compared to two conventional benchmark schemes: the optimal UAV link transmission and the IRS link transmission. The simulation results validate the theoretical derivation and demonstrate the superiority of the proposed scheme over the benchmark schemes.},
DOI = {10.32604/cmes.2023.030872}
}