Unmanned aerial vehicle technology in IoE

Unmanned aerial vehicle (UAV) air-ground communication is an important part of our country’s major project of advancing the integrated information network of the world. The wireless communication platform based on UAV provides an effective low-cost wireless connection for IoT sensor nodes. Compared with the ground IoT communication platform, the low-altitude UAV wireless communication systems have the advantages of fast deployment, low cost, on-demand deployment, flexible configuration, and better communication channel quality brought by short-range line-of-sight connections. On the other hand, the high mobility and energy limitation of drones bring new challenges to UAV wireless communication. First, an UAV swarm together with a large-scale heterogeneous Internet of Things (IoT) network that consists of macro cells and energy-constrained IoT transmitters (IoT-Ts) is investigated. The UAVs are utilized as flying robot swarms that intelligently transfer energy to the energy-constrained IoT-Ts on the ground. Each IoT-T has an associated IoT device (IoT-D) that is placed with a fixed distance in a random direction. The transmission probability of the energy-constrained IoT-Ts is derived by considering one-slot charging and two-slot charging based on three dimensional (3D) locations, respectively. The coverage probability of each type of IoT-Ds is investigated, and the energy efficiency is derived by considering the transmission power of the active IoT-Ts and the effect of the association biasing factor. Moreover, we maximize the energy efficiency by deploying the optimal density of IoT-Ts. Simulation results are conducted to validate the correctness of our theoretical analysis, and the results illustrate insightful effects of the network parameters, and the helpful guidelines for practical UAV swarms and IoT system design. Next, we study an UAV-aided nonorthogonal multiple access (NOMA) multiway relaying networks (MWRNs). Multiple terrestrial users aim to exchange their mutual information via an amplify-and-forward (AF) UAV relay. Specifically, the realistic assumption of the residual hardware impairments (RHIs) at the transceivers is taken into account. To evaluate the performance of the considered networks, we derive the analytical expressions for the achievable sum-rate (ASR). In addition, we carry out the asymptotic analysis by invoking the affine expansion of the ASR in terms of high signal-to-noise ratio (SNR) slope and high SNR power offset. Numerical results show that: 1) Compared with orthogonal multiple access (OMA), the proposed networks can significantly improve the ASR since it can reduce the time slots from [(M-1)/2+1 to 2; and 2) RHIs of both transmitter and receiver have the same effects on the ASR of the considered networks. Finally, in this chapter, we propose a unified framework for hybrid satellite/unmanned aerial vehicle (HS-UAV) terrestrial NOMA networks, where satellite aims to communicate with ground users with the aid of a decode-forward (DF) UAV relay by using NOMA protocol. All users are randomly deployed to follow a homogeneous Poisson point process (PPP), which is modeled by the stochastic geometry approach. To reap the benefits of satellite and UAV, the links of both satellite-to-UAV and UAV-to-ground user are assumed to experience Rician fading. More practically, we assume that perfect channel state information (CSI) is infeasible at the receiver, as well as the distance-determined path-loss. To characterize the performance of the proposed framework, we derive analytical approximate closed-form expressions of the outage probability (OP) for the far user and the near user under the condition of imperfect CSI. Also, the system throughput under delay-limited transmission mode is evaluated and discussed. In order to obtain more insights, the asymptotic behavior is explored in the high signal-to-noise ratio (SNR) region and the diversity orders are obtained and discussed. To further improve the system performance, based on the derived approximations, we optimize the location of the UAV to maximize the sum rate by minimizing the average distance between the UAV and users. The simulated numerical results show that: i) there are error floors for the far and the near users due to the channel estimation error; ii) the outage probability decreases as the Rician factor K increasing, iii) the outage performance and system throughput performance can be further improved considerably by carefully selecting the location of the UAV.