arXiv subjects

Xianzhen Guo

Publications and source records attributed to Xianzhen Guo.

5 recordsLinked to original sources

arXiv2025

User Equipment Assisted Localization for 6G Integrated Sensing and Communication

This paper investigates user equipment (UE) assisted device-free networked sensing in the sixth-generation (6G) integrated sensing and communication (ISAC) system, where one base station (BS) and multiple UEs, such as unmanned aerial vehicles (UAVs), serve as anchors to cooperatively localize multiple passive targets based on the range information. Three challenges arise from the above scheme. First, the UEs are not perfectly synchronized with the BSs. Second, the UE (anchor) positions are usually estimated by the Global Positioning System (GPS) and subject to unknown errors. Third, data association is challenging, since it is hard for each anchor to associate each rang estimation to the right target under device-free sensing. We first tackle the above three challenges under a passive UE based sensing mode, where UEs only passively hear the signals over the BS-target-UE paths. A two-phase UE assisted localization protocol is proposed. In Phase I, we design an efficient method to accurately estimate the ranges from the BS to the targets and those from the BS to the targets to the UEs in the presence of synchronization errors between the BS and the UEs. In Phase II, an efficient algorithm is proposed to localize the targets via jointly removing the UEs with quite inaccurate position information from the anchor set and matching the estimated ranges at the BS and the remaining UEs with the targets. Next, we also consider an active UE based sensing mode, where the UEs can actively emit signals to obtain additional range information from them to the targets. We show that this additional range information can be utilized to significantly reduce the complexity of Phase II in the aforementioned two-phase localization protocol. Numerical results show that our proposed UE assisted networked sensing scheme can achieve very high localization accuracy.

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arXiv2022

Trajectory Optimization of Cellular-Connected UAV for Information Collection and Transmission

In this paper, we consider a cellular-connected unmanned aerial vehicle (UAV) with an information collection and transmission mission for multiple ground targets. Specifically, the UAV is required to collect a fixed amount of information of each target by hovering at a pre-determined location (via e.g., photography/videography/sensing), and transmit all the collected information to the cellular network during its flight. We aim to jointly optimize the UAV's trajectory and the information collection order of the ground targets to minimize the mission completion time. The formulated problem is NP-hard due to the need of visiting the information collection locations for all targets; moreover, the UAV's trajectories over different time durations are coupled in non-convex constraints for ensuring information transmission completion. To handle this difficult problem, we first propose a structured communication protocol between the UAV and the cellular network, which decouples the UAV's trajectory designs in different time durations. Then, under the proposed protocol, we establish an equivalent graph-based model for the considered problem, and devise a low-complexity algorithm for finding an approximate solution by exploiting the problem structure and leveraging graph theory. Numerical results show that our proposed design achieves efficient information collection and transmission, and outperforms various benchmark schemes.

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arXiv2020

Performance Analysis for the CMSA/CA Protocol in UAV-based IoT network

UAV-based base station (UBS) has played an important role in the air-ground integration network due to its high flexibility and nice air-ground wireless channels. Especially in Internet of Things (IoT) services, UBS can provide an efficient way for data collection from the IoT devices. However, due to the continuous mobility of UBS, the communication durations of devices in different locations with the UBS are not only time-limited, but also vary from each other. Therefore, it is a challenging task to analyze the throughput performance of the UAV-based IoT network. Accordingly, in this paper, we consider an air-ground network in which UAV flies straightly to collect information from the IoT devices based on CSMA/CA protocol. An analytical model analyzing the performance of this protocol in the network is proposed. In detail, we set up the system model for the network, and propose a new concept called quitting probability. Then, a modified Markov chain model integrating the quitting probability is introduced to describe the transmission state transition process and an accurately theoretical analysis of saturation throughput is given. In addition, the effects of the network parameters are discussed in the simulation section.

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arXiv2020

Joint Placement Optimization and RNC in UAV-based Wireless Multicast Networks

Random network coding (RNC) is an efficient coding scheme to improve the performance of the broadband networks, especially for multimedia applications which are popular in 5G network. However, it is a challenging work to transmit the real time media data because of the time limitation and wide band requirement. Moreover, the topology of the network changes due to users' movement, causing huge channel heterogeneity in large wireless network area. In this case, the fixed macro base station (BS) or access point may not fit the real-time user distributions. Accordingly, the UAV-based BS with high mobility can provide flexible service by adjusting it position according to users' locations to fit the dynamic topology of the network. Therefore, in this paper, we propose a UAV-based adaptive RNC (UARNC) scheme that jointly optimizes the UAV's location and RNC packet scheduling to maximize the throughput in a multicast network while guaranteeing the service quality of the bottleneck users. This problem is formulated as an optimization problem, and the greedy scheduling techniques and particle swarm optimization (PSO) algorithm are adopted to solve it. Finally, the simulation results prove the effectiveness of the proposed scheme.

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arXiv2020

Performance Analysis and Optimization for the MAC Protocol in UAV-based IoT Network

Unmanned aerial vehicles (UAVs) have played an important role in air-ground integration network. Especially in Internet of Things (IoT) services, UAV equipped with communication equipments is widely adopted as a mobile base station (BS) for data collection from IoT devices on the ground. In this paper, we consider an air-ground network in which the UAV flies straightly to collect information from the IoT devices in a 2-D plane based on the CSMA/CA protocol. Due to UAV's continuous mobility, the communication durations of devices in different locations with UAV are not only time-limited, but also vary from each other. To analyze the throughput performance of uplink multiple access control (MAC) protocol, we propose a new analysis model to deal with the communications heterogeneity in the network. Firstly, we divide the devices in the coverage into different clusters according to their communication durations. Then, a quitting probability indicating the probability that a device quits the UAV's coverage at each time slot is clarified. A modified three-dimensional Markov chain model adopting the quitting probability and cluster division is developed for the performance analysis. Besides, we also propose a modified CSMA/CA protocol which fully considers the heterogeneity of the access time and adaptively allocates the time resource among the devices in different clusters. Finally, the effects of retry limit, initial contention window size, the density of the devices, UAVs speed and coverage area are discussed in the simulation section.

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