Open AccessEnhanced signalling provisioning for UAV‐enabled MEC: A GWFRFT‐based energy‐spreading transmission approach
Author(s) -
Li Chengfang,
Fang Xiaojie,
Zhou Xiaokang,
Mei Lin,
Sha Xuejun
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.1219
Subject(s) - computer science , robustness (evolution) , fading , computer network , quality of service , signalling , provisioning , transmission (telecommunications) , real time computing , channel (broadcasting) , telecommunications , biochemistry , chemistry , gene , economics , microeconomics
With the high mobility, flexibility and manoeuvrability, unmanned aerial vehicles (UAVs)‐enabled mobile edge computing (MEC) plays an important role in many applications that lack of available terrestrial infrastructures, such as disaster response, emergency relief and military scenarios. However, the high mobility of UAVs may severely degrade the implementation of UAV‐enabled MEC in computation‐intensive or delay‐sensitive scenarios from a physical layer signalling perspective, e.g. frequency selective fading effect caused by the low altitude and low elevation angle routes of UAVs. In this study, a generalised weighted‐type fractional Fourier transform (GWFRFT) based signal energy‐spreading transmission (EST) scheme is proposed for signalling and quality of service (QoS) provisioning for UAV‐enabled MEC. In the proposed scheme, the communication signal energy is redistributed evenly at the time‐frequency plane to enhance the robustness of UAV communications against the severe fading channels. The signalling provisioning mechanism of the GWFRFT‐EST scheme is analysed and simulated under poor air‐to‐ground channels with low Rician K ‐factor. Simulation results show that the proposed method greatly improves the bit error rate performance with a negligible computational complexity increase.