In this paper, we consider a single-cell cellular network with a number of cellular users (CUs) and unmanned aerial vehicles (UAVs), in which multiple UAVs upload their collected data to the base ...station (BS). Two transmission modes are considered to support the multi-UAV communications, i.e., UAV-to-network (U2N) and UAV-to-UAV (U2U) communications. Specifically, the UAV with a high signal-to-noise ratio (SNR) for the U2N link uploads its collected data directly to the BS through U2N communication, while the UAV with a low SNR for the U2N link can transmit data to a nearby UAV through underlaying U2U communication for the sake of quality of service. We first propose a cooperative UAV sense-and-send protocol to enable the UAV-to-X communications, and then formulate the subchannel allocation and UAV speed optimization problem to maximize the uplink sum-rate. To solve this NP-hard problem efficiently, we decouple it into three sub-problems: U2N and cellular user (CU) subchannel allocation, U2U subchannel allocation, and UAV speed optimization. An iterative subchannel allocation and speed optimization algorithm (ISASOA) is proposed to solve these sub-problems jointly. The simulation results show that the proposed ISASOA can upload 10% more data than the greedy algorithm.
Due to the capability of providing flexible network coverage, unmanned aerial vehicles (UAVs) are a promising solution to support the Internet‐of‐Things (IoT) applications, especially for the area ...without terrestrial network coverage. In this paper, a UAV‐assisted IoT network is considered, where a UAV serves as an aerial base station to serve ground IoT devices. To support the massive access, grant‐free non‐orthogonal communications are also adopted, where packets generated by IoT devices can skip the handshake process and share a channel with other packets for transmission. With the aim to maintain the information freshness, the age of information (AoI) for the network is first derived, and an AoI minimization problem is formulated as a Stackelberg game where the UAV is the leader and ground IoT devices are followers. However, solving such a problem is challenging as the number of involved followers is large. To simplify the problem, a mean‐field game based approach is proposed, where the average behaviours of followers are considered instead of individual strategies. Simulation results show that the computational complexity of the proposed scheme is almost unchanged with the number of IoT devices while the performance is close to the optimal one.
The effectiveness and cost are always top factors for policy-makers to decide control measures and most measures had no pre-test before implementation. Due to the COVID-19 pandemic, human activities ...are largely restricted in many regions in India since mid-March of 2020, and it is a progressing experiment to testify effectiveness of restricted emissions. In this study, concentrations of six criteria pollutants, PM10, PM2.5, CO, NO2, ozone and SO2 during March 16th to April 14th from 2017 to 2020 in 22 cities covering different regions of India were analysed. Overall, around 43, 31, 10, and 18% decreases in PM2.5, PM10, CO, and NO2 in India were observed during lockdown period compared to previous years. While, there were 17% increase in O3 and negligible changes in SO2. The air quality index (AQI) reduced by 44, 33, 29, 15 and 32% in north, south, east, central and western India, respectively. Correlation between cities especially in northern and eastern regions improved in 2020 compared to previous years, indicating more significant regional transport than previous years. The mean excessive risks of PM reduced by ~52% nationwide due to restricted activities in lockdown period. To eliminate the effects of possible favourable meteorology, the WRF-AERMOD model system was also applied in Delhi-NCR with actual meteorology during the lockdown period and an un-favourable event in early November of 2019 and results show that predicted PM2.5 could increase by only 33% in unfavourable meteorology. This study gives confidence to the regulatory bodies that even during unfavourable meteorology, a significant improvement in air quality could be expected if strict execution of air quality control plans is implemented.
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•The effect of restricted human activities due to the COVID-19 pandemic in India on air quality in 22 cities was estimated.•PM2.5 had maximum reduction in most regions.•Correlation between cities especially in northern and eastern regions improved in 2020 compared to previous years.•The substantial reduction in concentrations resulted in a 4 times reduction in total ER.•PM2.5 could increase due to unfavourable meteorology but the average concentration would still be under CPCB limits.
In this letter, we consider an unmanned aerial vehicle (UAV) relay network, where the UAV works as an amplify-and-forward relay. We optimize the trajectory of UAV, the transmit power of UAV, and the ...mobile device by minimizing the outage probability of this relay network. The analytical expression of outage probability is derived first. A closed-form low-complexity solution with joint trajectory design and power control is proposed to solve this non-convex problem. Simulation results show that the outage probability of the proposed solution is significantly lower than that of the fixed power relay and circle trajectory for the UAV relay.
Long-term air pollution data with high temporal and spatial resolutions are needed to support the research of physical and chemical processes that affect the air quality, and the corresponding health ...risks. However, such datasets were not available in China until recently. For the first time, this study examines the spatial and temporal variations of PM2.5, PM10, CO, SO2, NO2, and 8h O3 in 31 capital cities in China between March 2013 and February 2014 using hourly data released by the Ministry of Environmental Protection (MEP) of China. The annual mean concentrations of PM2.5 and PM10 exceeded the Chinese Ambient Air Quality Standards (CAAQS), Grade I standards (15 and 40μg/m3 for PM2.5 and PM10, respectively) for all cities, and only Haikou, Fuzhou and Lasa met the CAAQS Grade II standards (35 and 70μg/m3 for PM2.5 and PM10, respectively). Observed PM2.5, PM10, CO and SO2 concentrations were higher in cities located in the North region than those in the West and the South-East regions. The number of non-attainment days was highest in the winter, but high pollution days were also frequently observed in the South-East region during the fall and in the West region during the spring. PM2.5 was the largest contributor to the air pollution in China based on the number of non-attainment days, followed by PM10, and O3. Strong correlation was found between different pollutants except for O3. These results suggest great impacts of coal combustion and biomass burning in the winter, long range transport of windblown dust in the spring, and secondary aerosol formation throughout the year. Current air pollution in China is caused by multiple pollutants, with great variations among different regions and different seasons. Future studies should focus on improving the understanding of the associations between air quality and meteorological conditions, variations of emissions in different regions, and transport and transformation of pollutants in both intra- and inter-regional contexts.
•Temp-spatial variations of air pollutants in 31 Chinese cities were analyzed.•Major cities in China experience severe air pollution.•Significant temp-spatial differences in criteria air pollutants were observed.•Strong correlation was found between different pollutants except for O3.•China’s pollution is caused by multi-pollutants with temp-spatial variations.
The North China Plain (NCP) and the Yangtze River Delta (YRD) in China have been experiencing severe particulate matter (PM) pollution problems associated with the rapid economic growth and the ...accelerated urbanization. In this study, hourly mass concentrations of PM2.5 and PM10 during June 1st–August 31st, 2013 were collected in 13 cities located in or adjacent to the NCP region and 20 cities located in the YRD region. The overall average PM2.5 and PM10 concentrations were 77.0 μg/m3 and 136.2 μg/m3 in the NCP region, respectively, and 42.8 μg/m3 and 74.9 μg/m3 in the YRD region, respectively. The frequencies of occurrence of concentrations exceeding the China's Ambient Air Quality Standard (AAQS) (BG3095-12) Grade I standards were 83% for PM2.5 and 93% for PM10 in the NCP region, and 51% for PM2.5 and 66% for PM10 in the YRD region. Strong temporal correlation for both PM2.5 and PM10 between cities within 250 km was frequently observed. PM2.5 was found to be negatively associated with wind speed. On the PM2.5 episode days (when the 24 h PM2.5 concentration is greater than 75 μg/m3), average PM2.5 concentrations were 2–4 times greater compared to the non-episode days. The PM2.5 to PM10 ratio increased from 0.50 (0.57) on the non-episode days to 0.64 (0.64) on the episode days in the NCP (YRD) region. No distinct weekday/weekend difference was observed for PM2.5, PM10, and other gaseous pollutants (CO, SO2, NO2, and O3) in all cities. The results presented in this paper will serve as an important basis for future regional air quality modeling and source apportionment studies.
•Summertime PM2.5 and PM10 in the NCP and YRD regions of China were analyzed.•Average PM2.5 and PM10 concentrations are 77.0 and 136.2 μg/m3 in the NCP region.•Average PM2.5 and PM10 concentrations are 42.8 and 74.9 μg/m3 in the YRD region.•Strong temporal correlation between cities within 250 km is found.•PM2.5 concentrations on episode days are 2–4 times greater than non-episode days.
In this paper, we consider a single-cell multi-user orthogonal frequency division multiple access (OFDMA) network with one unmanned aerial vehicle (UAV), which works as an amplify-and-forward relay ...to improve the quality-of-service (QoS) of the user equipments (UEs) in the cell edge. Aiming to improve the throughput while guaranteeing the user fairness, we jointly optimize the communication mode, subchannel allocation, power allocation, and UAV trajectory, which is an NP-hard problem. To design the UAV trajectory and resource allocation efficiently, we first decompose the problem into three subproblems, i.e., mode selection and subchannel allocation, trajectory optimization, and power allocation, and then solve these subproblems iteratively. Simulation results show that the proposed algorithm outperforms the random algorithm and the cellular scheme.
In this paper, we study an intelligent omni-surface (IOS)-assisted downlink communication system, where the link quality of a mobile user (MU) can be improved with a proper IOS phase shift design. ...Unlike the intelligent reflecting surface (IRS) in most existing works that only forwards the signals in a reflective way, the IOS is capable to forward the received signals to the MU in either a reflective or a transmissive manner, thereby enhancing the wireless coverage. We formulate an IOS phase shift optimization problem to maximize the downlink spectral efficiency (SE) of the MU. The optimal phase shift of the IOS is analysed, and a branch-and-bound based algorithm is proposed to design the IOS phase shift in a finite set. Simulation results show that the IOS-assisted system can extend the coverage significantly when compared to the IRS-assisted system with only reflective signals.
Device-to-device (D2D) communication, which enables direct communication between nearby mobile devices, is an attractive add-on component to improve spectrum efficiency and user experience by reusing ...licensed cellular spectrum in 5G system. In this paper, we propose to enable D2D communication in unlicensed spectrum (D2D-U) as an underlay of the uplink LTE network for further booming the network capacity. A sensing-based protocol is designed to support the unlicensed channel access for both LTE and D2D users. We further investigate the subchannel allocation problem to maximize the sum rate of LTE and D2D users while considering their interference to the existing Wi-Fi systems. Specifically, we formulate the subchannel allocation as a many-to-many matching problem with externalities, and develop an iterative user-subchannel swap algorithm. Analytical and simulation results show that the proposed D2D-U scheme can significantly improve the system sum rate.
In the current unmanned aircraft systems (UASs) for sensing services, unmanned aerial vehicles (UAVs) transmit their sensory data to terrestrial mobile devices over the unlicensed spectrum. However, ...the interference from surrounding terminals is uncontrollable due to the opportunistic channel access. In this paper, we consider a cellular Internet of UAVs to guarantee the Quality-of-Service (QoS), where the sensory data can be transmitted to the mobile devices either by UAV-to-Device (U2D) communications over cellular networks, or directly through the base station (BS). Since UAVs' sensing and transmission may influence their trajectories, we study the trajectory design problem for UAVs in consideration of their sensing and transmission. This is a Markov decision problem (MDP) with a large state-action space, and thus, we utilize multi-agent deep reinforcement learning (DRL) to approximate the state-action space, and then propose a multi-UAV trajectory design algorithm to solve this problem. Simulation results show that our proposed algorithm can achieve a higher total utility than policy gradient algorithm and single-agent algorithm.
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