A Survey on Channel Sounding Technologies and Measurements for UAV-Assisted Communications

Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian applications, where a stable communication link is vital for safe flight control and robust data transmission. To develop a reliable UAV communication system, it is necessary to deeply understand the UAV channel characteristics and establish accurate channel models. Channel sounding is the most effective way to obtain realistic channel characteristics and validate the theoretical channel model. However, the studies on UAV channel sounding are still insufficient in terms of system design and data processing due to the complexity of developing a UAV channel sounder. Different from the terrestrial channel sounders, the implementation of a UAV channel sounder is tortured by the limited battery life and payload capacity of the UAV platform. The sounding scheme and data post-processing also need to be specially designed for highly dynamic UAV channels. So far, most existing survey studies on UAV channels focus on modeling methodology and model presentation. To fill this gap, this paper provides a comprehensive survey on the design of the UAV channel sounder, in terms of the hardware scheme, sounding signal, time synchronization, calibration, and data post-processing. Current issues and potential research topics behind existing sounding technologies and measurement campaigns are analyzed. Moreover, future challenges and open issues are also discussed.</p

Tunable Multi-Frequency Optoelectronic Oscillator Based on a Microwave Photonic Filter and an Electrical Filter

Abstract We propose and experimentally demonstrate a multi-frequency optoelectronic oscillator (OEO) based on phase-modulation to intensity-modulation (PM-IM) conversion. A microwave photonic filter (MPF) incorporating an optical fiber Bragg grating Fabry-Perot (FBG-FP) filter and an electrical yttrium iron garnet (YIG) filter in two branches are used to select the oscillation modes of the OEO. By adjusting the wavelength of laser source or the central frequency of YIG filter, two frequencies can be tuned independently within a wide range. The single sideband (SSB) phase noises of the generated frequencies are measured experimentally. Moreover, the OEO shows potential ability to achieve more frequencies oscillation by multiplexing more optical and electrical filters.</jats:p

Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China

The interaction between human activity and landscape pattern has been a hot research topic during the last few decades. However, scholars used to measure human activity by social, economic and humanistic indexes. These indexes cannot directly reflect human activity and are not suitable for fine-grained analysis due to the coarse spatial resolution. In view of the above problems, this paper proposes a method that obtains the intensity of human activity from GPS trajectory data, collects landscape information from remote sensing images and further analyzes the interaction between human activity and landscape pattern at a fine-grained scale. The Lijiang River Basin is selected as the study area. Experimental results show that human activity and landscape pattern interact synergistically in this area. Built-up land and water boost human activity, while woodland restrains human activity. The effect of human activity on landscape pattern differs by the land cover category. Overall, human activities make natural land, such as woodland and water, scattered and fragmented, but cause man-built land, such as built-up land and farmland, clustered and regular. Nevertheless, human activities inside and outside urban areas are the opposite. The research findings in this paper are helpful for designing and implementing sustainable management plans

Accurate Indoor Localization Based on CSI and Visibility Graph

Passive indoor localization techniques can have many important applications. They are nonintrusive and do not require users carrying measuring devices. Therefore, indoor localization techniques are widely used in many critical areas, such as security, logistics, healthcare, etc. However, because of the unpredictable indoor environment dynamics, the existing nonintrusive indoor localization techniques can be quite inaccurate, which greatly limits their real-world applications. To address those problems, in this work, we develop a channel state information (CSI) based indoor localization technique. Unlike the existing methods, we employ both the intra-subcarrier statistics features and the inter-subcarrier network features. Specifically, we make the following contributions: (1) we design a novel passive indoor localization algorithm which combines the statistics and network features; (2) we modify the visibility graph (VG) technique to build complex networks for the indoor localization applications; and (3) we demonstrate the effectiveness of our technique using real-world deployments. The experimental results show that our technique can achieve about 96% accuracy on average and is more than 9% better than the state-of-the-art techniques