Daqing Huang

Achieving autonomous and reliable unmanned aerial vehicle (UAV) swarm applications requires a flexible and efficient communication network structure. Unfortunately, the high-speed movement of UAVs leads to drastic changes in wireless links and topology structures, posing significant challenges to reliable data transmissions. Geographic routing protocols exhibit better adaptability to highly dynamic network topologies and have garnered extensive attention in UAV networks. However, existing works did not effectively address the impact of factors such as link state fluctuations and routing holes on the performance of these protocols. To this end, by considering future evolution of link states, this paper proposes a reinforcement-learning-based geographic routing protocol (Evo-QGeo) and introduces a new routing hole bypass method. Thanks to the evaluation of future evolution of link states and the multihop optimization capability of reinforcement learning, the end-to-end packet reception rate of Evo-QGeo is improved by up to 11.81~44.61% compared to existing ones. Meanwhile, the energy consumption is reduced by up to 36.94~74.47%, the latency is reduced by up to 21.63~38.68%, and the end-to-end expected transmission count is reduced by up to19.60~26.10%. This makes Evo-QGeo more suitable for highly dynamic UAV networks.

Performance of flying ad hoc networks (FANETs) largely depends on the routing protocol used. Applying conventional traditional mobile ad hoc networks (MANETs) routing frameworks to FANETs requires a careful assessment of their compatibility. Crucially, these protocols must be robust enough to handle the volatile link states and rapid topological shifts inherent in high-mobility UAV clusters. Although there have been many works that evaluated and compared the performance of different MANET routing protocols in FANET scenarios through simulation, they ignored the comparative evaluation of various pathfinding schemes across diverse movement patterns. This research addresses this limitation by examining the efficiency of three representative protocols under distinct mobility scenarios using extensive simulations. The findings demonstrate that the selected mobility model influences not only the protocol’s efficiency but also the comparative ranking of different routing protocols. The conclusion of which routing protocol is better or worse obtained under a specific mobility model is usually not universal and only holds for the specific mobility model used. These conclusions will be more helpful for selecting appropriate routing protocols to adapt to the complex and ever-changing UAV network application scenarios.

Efficient and reliable data collection is crucial for unmanned aerial vehicles (UAVs) assisted low-power wireless networks. However, existing works on UAV-assisted data collection seldom consider how to ensure reliable communication. Experimental studies have shown that changes in UAV's flight direction and potential interference in surrounding environments will impact the range of reliable communication. In light of this, this paper formulates the packet reception ratio (PRR) under harsh environments with interference, by considering the impact of UAV movement on low-power links and factors affecting the relationship between physical layer parameters and PRR. Then, a three-dimensional (3D) spatial partition model for UAV assisted low-power wireless networks is proposed. Experimental results show that compared with existing models, the proposed one reduces the PRR estimation error by up to 77.58%. The proposed spatial partition model accurately distinguishes the connected region, transitional region, and disconnected region, with an accuracy rate exceeding 95% under different flight modes. To verify the practicality of the proposed spatial partition model, its application for UAV-assisted data collection is evaluated through simulations. The results show that compared with existing models, the proposed one can effectively improve the efficiency of data collection.

Accurate and reliable channel modeling is crucial for uncrewed aerial vehicles (UAVs)-assisted low-power wireless networks. However, existing research has shown that existing channel models are not accurate in this scenario. This article evaluates existing channel models and analyzes the factors impacting the accuracy of channel modeling. The results show that the path loss exponent (PLE) and antenna irregularity will affect the path loss under different flight modes. Based on the above finding, by considering the PLE and antenna irregularity, this article proposes a channel modeling method based on the relative position of the UAV and ground node. The experimental results show that the proposed model is suitable for UAV-assisted low-power wireless networks. The proposed method greatly reduces the estimation error of path loss under the premise of low computation overhead. Compared with existing channel models, thanks to more comprehensive considerations of the proposed method, the estimation error of the model established by the proposed method is reduced by 4.42%–92.78% under the ground-to-air (GA) channel and 13.23%–82.12% under the air-to-ground (AG) channel.

Accurate wireless channel modeling is essential for unmanned aerial vehicle (UAV) assisted wireless sensor networks (WSNs). However, existing path loss models suitable for UAV assisted WSNs are not accurate enough and usually can only characterize the channel under specific flight trajectories. In this letter, by introducing the impact of radio irregularity, a novel channel modeling methodology is proposed, which attempts to determine the bounds of path loss for UAV assisted WSNs. Experimental results show that the bounds of path loss estimated by the proposed modeling methodology are capable of covering 94.7% of the measured points in average under different UAV trajectories and environments. This means that the proposed methodology can be applied to various different scenarios, which could provide more general design and analysis tools for UAV assisted WSNs.

Multichannel communication has great potential in environments with unknown interference patterns. However, existing link quality metrics and models are generally established and verified under a single-channel scenario, which does not consider the impacts of radio interference and channel change. Therefore, it is hard to directly judge whether these metrics and models are still valid under a multichannel scenario. This paper empirically analyzes the applicability of popular link quality metrics and models in multiple channels with different interference levels. Results show that the link quality estimation (LQE) capability of traditional metrics will be affected by the interference level of the channel, which makes the conclusions obtained under a single-channel scenario no longer valid. Meanwhile, traditional LQE models are basically not adaptive to radio interference and channel change. They are only valid for channels with similar interference under which they are modeled. If these models are directly used under a multichannel scenario, the link quality will be overestimated inevitably. In other words, traditional LQE metrics and models cannot be directly used in the multichannel scenario. It is necessary to deeply analyze the statistical characteristics of popular link quality metrics in multiple typical channels and design channel and interference adaptive metrics and models to support effective multichannel communication.

The heating and impact of arc and droplet acting on the weld pool lead to the transfer of mass, heat, and momentum, which affects the dynamic behavior of the weld pool and the microstructure in the P-GMAW process. In this paper, an image processing program is used to extract the dynamic behavior characteristics of the droplet transition and the weld pool in high-speed photography. The influence of the current waveform on the arc pressure and the impact of the droplet is quantitatively analyzed with different parameters. The dynamic behavior of the weld pool and the microstructure under different current waveform conditions are further studied. The internal relation of current waveform parameters to weld pool behavior and weld microstructure was expounded. The results show that the droplet impact is positively correlated with the pulse peak current. The rectangular wave pulse has a more significant droplet impact than the exponential wave with the same waveform parameters. The impact of droplet transition on the weld pool enhances the convective intensity of the weld pool. It slows down the cooling rate of the solidified weld microstructure below the tail of the weld pool, increasing the grain size of the weld microstructure.

A three-stage padding configuration providing a larger continuous virtual aperture and achieving more degrees-of-freedom (DOFs) for the direction-of-arrival (DOA) estimation is presented. The improvement is realized by appropriately cascading three-stages of an identical inter-element spacing. Each stage advantageously exhibits a continuous virtual array, which subsequently produces a hole-free resulting uniform linear array. The geometrical approach remains applicable for any existing sparse array structures with a hole-free coarray, as well as designed in the future. In addition to enlarging the continuous virtual aperture and DOFs, the proposed design offers flexibility so that it can be realized for any given number of antennas. Moreover, a special padding configuration is demonstrated, which further increases the number of continuous virtual sensors. The precise antenna locations and the number of continuous virtual positions are benefited from the closed-form expressions. Experimental works are carried out to demonstrate the effectiveness of the proposed configuration.

Most existing unmanned aerial vehicle (UAV) assisted wireless sensor network (WSN) studies usually assume that using a large SNR or a short distance can ensure good link quality. However, they don't consider the actual characteristics of UAV assisted WSN. In this paper, spatial characteristics of wireless links, link quality indicating capabilities of physical layer metrics and symmetry of uplink and downlink are analyzed by comparing the measured data of UAV assisted WSN and traditional WSN. The results show that link characteristics of UAV assisted WSN have changed significantly compared with those of traditional WSN. Firstly, connected region of the three traditional communication regions (connected region, transitional region, and disconnected region) is significantly compressed and even no longer exists, which makes that short distance can no longer guarantee reliable communication. Secondly, traditional physical layer metrics such as RSSI, SNR and LQI are no longer valid and even become deceptive, which may lead to wrong judgment of link quality. Finally, there is obvious overall asymmetry between uplink and downlink of UAV assisted WSN, and the quality of downlink is significantly higher than that of the uplink. The discovery of these new features would have great significance on guiding the design of UAV assisted WSN.