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Rate Splitting on Mobile Edge Computing for UAV-aided IoT Systems
IEEE Transactions on Cognitive Communications and Networking  (IF4.341),  Pub Date : 2020-12-01, DOI: 10.1109/tccn.2020.3012680
Rui Han, Yongqing Wen, Lin Bai, Jianwei Liu, Jinho Choi

In the Internet of Things (IoT), numerous low complexity and energy constrained devices are employed to collect and transmit data simultaneously, where the unmanned aerial vehicle (UAV) is an efficient means to relay the signals. Considering the limited power and computational capability of UAV, mobile edge computing (MEC) is carried out to enhance the usage of UAV-aided IoT networks. In order to develop robust UAV-aided MEC systems, energy efficient transmission schemes and low-latency computational resource allocation become crucial to cope with the energy limitation of UAV and computing delay of MEC. In this paper, we develop UAV-aided MEC systems, where UAVs collect data from IoT devices and then transmit to MEC-based access points for computation. In order to minimize the energy consumption of a UAV in the centralized and distributed MEC computation modes under the constraints of transmission rate and computational time, respectively, a joint rate splitting problem is formulated to optimally allocate rates for transmission links between two antenna arrays on the UAV. In addition, the altitude of UAV is analyzed and designed. From simulation results, it shows the proposed architecture is able to provide robust and high quality transmission rate for the UAV-aided MEC systems.