The Distributed Coordination Function (DCF) is the core of IEEE 802.11 standard and is applied routinely to contention-based vehicular network. Many existing backoff algorithms based on DCF are applied to develop the performance of wireless network and most of them work in saturated traffic load conditions, which are unlikely to be valid in practical wireless network. The study of the backoff algorithm under unsaturated traffic load conditions is still an open issue. In this paper, a dynamic adaptive success-collision (DASC) backoff algorithm is proposed to improve the performance of contentionbased vehicular network. As we know that the probability of collision reflects system performance, and the probability of collision is restricted by the variation of contention window (CW) size and it depends on the traffic loads. A threshold is defined to judge the low or high traffic loads. In addition, the DASC backoff algorithm takes proactive measures to optimize throughput and delay through decreasing CW after “S” times consecutive successful transmissions and increasing CW after “C” times consecutive collisions. The simulation results indicate that the proposed DASC backoff algorithm provides better performance in terms of throughput and delay than dynamic control backoff time algorithm (DCBTA), exponential linear backoff algorithm (ELBA) and binary exponential backoff (BEB) algorithm.

The angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of arrival (TOA), AOA has higher accuracy and is not sensitive to the time synchronization of the distributed sensors. However, there are few works focusing on three-dimensional (3-D) scenarios. Furthermore, although the maximum likelihood estimator (MLE) has a relatively high performance, its computational complexity is ultra-high. Therefore, it is hard to employ it in practical applications. This paper proposed two center of inscribed sphere-based methods for 3-D AOA positioning via multiple UAVs. The first method could estimate the source position and angle measurement noise at the same time by seeking the center of an inscribed sphere, called the CIS. Firstly, every sensor measures two angles, the azimuth angle and the elevation angle. Based on that, two planes are constructed. Then, the estimated values of the source position and the angle noise are achieved by seeking the center and radius of the corresponding inscribed sphere. Deleting the estimation of the radius, the second algorithm, called MSD-LS, is born. It is not able to estimate angle noise but has lower computational complexity. Theoretical analysis and simulation results show that proposed methods could approach the Cramér–Rao lower bound (CRLB) and have lower complexity than the MLE.

Jiangsu province is one of the economically strong provinces in east China. With the advance of the modernization process, the problem of air pollution in this area is facing a severe challenge under the common role of human activities and regional climate change. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates the change in air pollution (focusing on the air quality index (AQI), six ambient air pollutants nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter with aerodynamic diameters ≤10 μm (PM10) and ≤2.5 μm (PM2.5)) patterns for different periods in last 5 years. Different pollutants have different behavior identified in this studied which is helping for understanding the pattern of air quality. Short-term health advantages from the COVID-19 pandemic can be attributed to the reduction in air pollution and significant improvement in ambient air quality, which need the government to enact post-COVID environmental regulations.

The multipath fading and Doppler effect are well-known phenomena affecting channel quality in mobile wireless communication systems. Within this context, the emergence of reconfigurable intelligence surfaces (RISs) brings a chance to achieve this goal. RISs as a potential solution are considered to be proposed in sixth generation (6G). The core idea of RISs is to change the channel characteristic from uncontrollable to controllable. This is reflected by some novel functionalities with wave absorption and abnormal reflection. In this paper, the multipath fading and Doppler effect are characterized by establishing a mathematical model from the perspective of reflectors and RISs in different mobile wireless communication processes. In addition, the solutions that improve the multipath fading and Doppler effect stemming from the movement of mobile transmitter are discussed by utilizing multiple RISs. A large number of experimental results demonstrate that the received signal strength abnormal fluctuations due to Doppler effect can be eliminated effectively by real-time control of RISs. Meanwhile, the multipath fading is also mitigated when all reflectors deployed are coated with RISs.

Various types of service applications increase the amount of computing in vehicular networks. The lack of computing resources of the vehicle itself will hinder the improvement of network performance. Mobile edge computing (MEC) technology is an effective computing method that is used to solve this problem at the edge of network for multiple mobile users. In this paper, we propose the multi-user task offloading strategy based on game theory to reduce the computational complexity and improve system performance. The task offloading decision making as a multi-user task offloading game is formulated to demonstrate how to achieve the Nash equilibrium (NE). Additionally, a task offloading algorithm is designed to achieve a NE, which represents an optimal or sub-optimal system overhead. In addition, the vehicular communication simulation frameworks Veins, SUMO model and OMNeT++ are adopted to run the proposed task offloading strategy. Numerical results show that the system overhead of the proposed task offloading strategy can degrade about $24.19\%$ and $33.76\%$, respectively, in different scenarios.

The randomness property of wireless channels restricts the improvement of their performance in wireless networks. As a novel solution for overcoming this, a reconfigurable intelligent surface (RIS) was introduced to reshape wireless physical environments. Initially, the multi-path and Doppler effects are discussed in a case in which a reflector was considered to reflect the incident signal for wireless communication. Subsequently, the results for the transmission signal were analyzed when a reflector was coated with an RIS. Specifically, the multi-path fading stemming from the movement of the mobile transmitter was eliminated or mitigated by utilizing an RIS. Meanwhile, the Doppler effect was also reduced to restrain the rapid fluctuations in the transmission signal by using a tunable RIS in real time. The simulation results demonstrate that the magnitude and spectrum of the received signal can be regulated by an RIS. The multi-path fading and Doppler effect can be effectively mitigated when the reflector is coated with an RIS in wireless networks.