Most of the existing methods to evaluate the quality of panoramic content mainly focus on studying the quality evaluation of static panoramic images, rather than the more widely used dynamic panoramic videos. Also, the few panoramic video quality metrics that are available have obvious weaknesses in terms of robustness. To this end, we propose a robust quality evaluator for panoramic videos (RQE-PV). First, a viewport prediction module is proposed by developing a multi-step fixation screening mechanism to simulate the characteristics of limited visual range and excavate the process of human eye movement. Further, both the temporal and spatial features are explored and fused for quality prediction. The superior robustness of the proposed method has been demonstrated on two public panoramic video databases.

Unmanned aerial vehicle (UAV) can serve as aerial base station to quickly restore the communication coverage of the disaster area, but finite energy poses a crucial challenge to UAV emergency communications. To maximize the average energy efficiency of UAV emergency communications, we propose the energy-efficient spectrum allocation and deployment (ESAD) scheme, which covers all disaster users and guarantees the quality of service (QoS) for users by deploying multiple UAVs. Based on the QoS requirement of user and graph coloring method, we propose the interference avoidance algorithm, which avoids interference among users served by the same UAV and interference among UAVs through user spectrum resource allocation and UAV spectrum management, respectively. Then, the ESAD scheme is proposed to achieve the maximum average energy efficiency of UAV while covering all disaster users. Simulation results show that compared with traditional schemes, the proposed scheme effectively reduces the number of deployed UAVs and improves the average energy efficiency of UAV emergency communications.

With the continuous improvement of spectrum efficiency and connection density requirements of internet of things (IoT) networks, the integration of non-orthogonal multiple access (NOMA) technology and unmanned aerial vehicle (UAV) communication technology has gradually become a hot research direction. In this paper, a UAV deployment and resource allocation strategy is proposed for the UAV-NOMA based IoT networks. The strategy aims to improve the user connection capability, and comprehensively considers multiple factors such as the UAV height optimization, the users’ transmit power allocation and subcarrier scheduling. Specifically, this proposed strategy is dominated by the genetic algorithm (GA) to achieve the collaborative scheduling of resources by combining power control and channel allocation sub-algorithms. The simulation results show that the proposed strategy has an excellent performance under a variety of system parameter changes, and the average user connection ratio is 10% higher than that of the comparison algorithm. This work provides an effective resource management solution for the UAV-NOMA based system in the future air-ground convergence communication scenario, and thus has good engineering practical value and promotion prospects.

In recent years, Internet of Things (IoT) develops rapidly all over the world, and the massive IoT equipment (IE) is envisioned to consume huge amount of energy, thus becoming the leading energy guzzler in future 6G communications. As the green energy technology, the time switching (TS) protocol can support the perpetual energy supply for the IE. Furthermore, orbital angular momentum (OAM) can provide the IE with new dimensional orthogonal resource. Therefore, this paper proposes the TS protocol based wireless-powered OAM communications for green IoT, which can transfer power and multiple independent information simultaneously with different OAM modes. For the energy-limited IE, we first design the framework of the TS protocol based wireless-powered OAM communications. Then, the capacity maximization problem is formulated with the quality-of-service requirement of the IE. Finally, we prove that the formulated capacity maximization problem is convex, and derive the closed-form expression of the optimal TS factor. Simulation results are presented to demonstrate the performance of the proposed TS protocol based wireless-powered OAM communications.

Due to the crowded three-dimensional structure, high building fire poses a great threat to the safety of people’s lives and property. Taking the advantages of maneuverability and flexibility, unmanned aerial vehicle (UAV) can provide emergency communication coverage for high buildings in fire scenarios, which effectively supports the evacuation and rescue of people. Thus, for high buildings in fire scenarios, this paper proposes the fire spread based UAV deployment (FSUD) scheme, which can be divided into vertical and horizontal UAV deployments. The non-steady state model of heat release rate, which is related with the fire spread diameter and fire height, is used to characterize the fire spread for the model establishment of vertical and horizontal UAV deployments. To track the fire, the vertical UAV deployment dynamically adjusts the floor number of UAV by discretizing the burning time of the fire. To cover the dense people on the rooftop of high buildings, the horizontal UAV deployment is given to maximize the UAV capacity. Simulation results show that the proposed FSUD scheme can efficiently determine the floor number in vertical direction, and achieve full coverage of people with the minimum UAV number.

As the most driven force of future 6G communications, Internet of Everything (IoE) requires energy-constrained IoE devices (IDs) to realize interconnection among users, information, and things. Wireless-powered orbital angular momentum (OAM) communications can be used for IDs to achieve simultaneous wireless power transfer and multiple independent information transmissions by different OAM modes. However, the practical blockage and access capability enhancement impose crucial challenges for wireless-powered OAM communications. Therefore, for blocked line-of-sight scenario, this paper proposes non-orthogonal multiple access (NOMA)-enhanced intelligent reflecting surface (IRS) for wireless-powered OAM communications by jointly optimizing power allocation and passive beamforming. First, we formulate the information capacity and harvested energy optimization problem under the constraints of unit-modulus reflecting phase shift, minimum power transfer requirement, and minimum information transmission demand. Then, the harvested energy is converted to the achievable capacity by the energy utilization for information transmission, thus forming the sum capacity maximization problem. Finally, we decompose the sum capacity maximization problem into three subproblems, and obtain the optimal power allocation and passive beamforming by iteration. Simulation results validate the proposed NOMA-enhanced IRS of wireless-powered OAM communications, and demonstrate that the joint power allocation and passive beamforming achieves better capacity performance than the other optimization schemes.

Due to maneuverability and Line-of-Sight (LoS) path, unmanned aerial vehicle (UAV) can serve as aerial base station to provide communication coverage and data collection for emerging Internet of Things (IoT) in the hotspot. However, limited spectrum resource and different Quality-of-Service (QoS) requirement impose critical challenges for UAV-aided IoT communications to cover massive IoT equipments (IEs). In this article, we propose the QoS-guaranteed multi-UAV coverage (QMC) scheme with interference management, which determines UAV deployment and spectrum resource allocation, to cover all ground IEs that have different QoS requirements. First, the interference management-based spectrum resource allocation (IMSA) algorithm, which utilizes the tabu search method of graph coloring, is proposed to avoid the interference between UAVs that have same IEs in their coverage. Then, we obtain the QoS-guaranteed single UAV placement (QSUP) algorithm to maximize the capacity of UAV while satisfying different QoS requirements for ground IEs. Finally, based on the IMSA and QSUP algorithms, the QMC scheme with interference management, which serves all ground IEs, is proposed to optimize the deployment of multiple UAVs for maximization of average UAV capacity. Simulation results demonstrate that compared with traditional schemes, the proposed QMC scheme achieves smaller UAV number and higher average UAV capacity due to the efficient interference management.

In space communications, the signal suffers a long-distance transmission and a high dynamic movement. The long-distance transmission causes a very low signal-to-noise ratio (SNR) and the high dynamic movement causes a high-accelerating Doppler-shift. To address the low SNR, the conventional strategy is long-time accumulation. However, during the long-time accumulation period, the high-accelerating Doppler-shift brings about the serious energy dispersion problem. In this paper, we propose one joint-comb-acquisition (JCA) scheme to address the energy dispersion problem. The proposed JCA scheme, which uses multiple accumulation periods to jointly construct a narrower comb-search-range, excludes most noise elements. Also, the theoretical analysis derives the closed-form expression for acquisition probability. Moreover, the simulation results demonstrate the significant increase of acquisition probability varies from 4.6 to 47.2 percents, as compared with the existing schemes.

In this study, the authors study the power efficiency optimisation in wireless‐powered full‐duplex relay (WFR) systems, where the entire transmission process can be partitioned into wireless power transfer phase (WP) and full‐duplex information transmission phase (FP). For WFR systems with same source transmit power, where the source transmit powers of WP and FP are same, they first prove that the power efficiency is a strictly concave function over the time‐switching factor, and an optimal time allocation scheme is proposed to maximise the power efficiency. Then, for the given time‐switching protocol, the optimal power allocation strategy is obtained by analysing the derivative of the power efficiency with respect to the transmit power. Finally, they propose the joint power and time allocation scheme. For WFR systems with different source transmit power, where the source transmit powers of WP and FP are different, the optimal time allocation scheme and optimal power allocation strategy are derived by studying the derivative of the power efficiency. Furthermore, the joint power and time allocation scheme is proposed to maximise the power efficiency. Simulation results are presented to validate the authors' proposed schemes for the WFR systems.

In this study, the authors investigate the bidirectional wireless information and power transfer (BWIPT) in decode‐and‐forward (DF) relay systems, where the bidirectional relay can decode and forward information from the user to the access point (AP), and assist the wireless power transfer from the AP to the user. The relay employs the power splitting (PS) protocol to coordinate the received signal energy for information transmission and energy harvesting. By converting the multi‐relay system information rate maximisation problem into a convex optimisation problem, the distributed power allocation scheme is obtained to maximise the information rate. Particularly, for single‐relay systems, the authors derive the closed‐form expression of the optimal PS factor, which can maximise the information rate. Simulation results show that the BWIPT for DF relay systems outperforms the BWIPT for amplify‐and‐forward relay systems.