Xidian University

About: Xidian University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Antenna (radio) & Computer science. The organization has 32099 authors who have published 38961 publications receiving 431820 citations. The organization is also known as: University of Electronic Science and Technology at Xi'an & Xīān Diànzǐ Kējì Dàxué.

Capacity of Cooperative Vehicular Networks with Infrastructure Support: Multiuser Case

Abstract: Capacity of vehicular networks with infrastructure support is both an interesting and challenging problem as the capacity is determined by the interplay of multiple factors including vehicle-to-infrastructure (V2I) communications, vehicle-to-vehicle (V2V) communications, density and mobility of vehicles, and cooperation among vehicles and infrastructure. In this paper, we consider a typical delay-tolerant application scenario with a subset of vehicles, termed Vehicles of Interest (VoIs), having download requests. Each VoI downloads a distinct large-size file from the Internet and other vehicles without download requests assist the delivery of the files to the VoIs. A cooperative communication strategy is proposed that explores the combined use of V2I communications, V2V communications, mobility of vehicles and cooperation among vehicles and infrastructure to improve the capacity of vehicular networks. An analytical framework is developed to model the data dissemination process using this strategy, and a closed-form expression of the achievable capacity is obtained, which reveals the relationship between the capacity and its major performance-impacting parameters such as inter-infrastructure distance, radio ranges of infrastructure and vehicles, sensing range of vehicles, transmission rates of V2I and V2V communications, vehicular density, and proportion of VoIs. Numerical result shows that the proposed cooperative communication strategy significantly boosts the capacity of vehicular networks, especially when the proportion of VoIs is low. Our results provide guidance on the optimum deployment of a vehicular network infrastructure and the design of a cooperative communication strategy to improve the capacity.

When UAV Meets IRS: Expanding Air-Ground Networks via Passive Reflection

Abstract: Thanks to their flexibility and mobility, unmanned aerial vehicles (UAVs) have been widely applied in wireless networks. However, UAV communications may suffer from blockage and eavesdropping in practical scenarios due to the complex environment. Taking the recent advances in intelligent reflecting surface (IRS) to reconfigure the propagation environments, in this article, we employ IRS to enhance the performance of UAV-aided air-ground networks. First, we overview the combination of UAV and IRS, by introducing the diverse applications of IRS and the appealing advantages of UAV, and highlighting the benefits of combining them. Then, we investigate two case studies where the UAV trajectory, the transmit beamforming and the IRS passive beamforming are jointly optimized. In the first case study, by equipping the IRS on a UAV, the average achievable rate of the relaying network is maximized. In the second one, the IRS is deployed to assist the UAV-ground communication while combating the adversarial eavesdropper. Simulation results are provided to demonstrate the performance enhancement resulting from combining UAV and IRS in air-ground networks. Finally, we shed light on some challenging issues to be resolved for practical implementations in this direction.

A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks

Abstract: With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. “Large-scale” means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed.