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The fifth generation (5G) communication has the potential to achieve ubiquitous positioning when integrated with a global navigation satellite system (GNSS). The device-to-device (D2D) communication, serving as a key technology in the 5G network, provides the possibility of cooperative positioning with high-density property. The mobile users (MUs)...
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The Internet of Things (IoT) is an emerging technology that provides services to any smart device at any place. Due to the large volume of data and dynamicity, the IoT environment faces challenges in terms of overloading and energy consumption. To resolve those issues, we proposed MISSION (MobIlity taSk Scheduling OffloadiNg) method to solve these...
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... The experimental results showed that the detection rate exceeded 98% [5]. Zhang et al. proposed an integrated GNSS/5G 3D localization scheme based on D2D communication, which improved the localization accuracy by about 58% over the GNSS localization results using time of arrival (TOA) and received signal strength (RSS) measurements in a 5G network using density space clustering with noise (DBSCAN) and particle filtering (PF) algorithms [6]. Klus et al. proposed a solution in the context of 5G and machine learning to improve the positioning accuracy in urban areas by obtaining the location of user equipment (UE) from beamforming radio signal strength (RSS) measurements and fusing them with GNSS-based positioning data to improve the overall positioning performance [7]. ...
With the large-scale use of BeiDou navigation and 5G technology worldwide, integrating BeiDou navigation and communication has become a hot research topic in navigation and positioning technology. Low-cost, miniaturized, and susceptible mixed-signal receivers will become the future receiver technology development trend. However, the current receiver technology still faces the challenge of further improving the positioning service capability and communication quality, which includes the lack of practical analysis of the compatibility between signals and the lack of mixed-signal processing capability of the receiver baseband key technology. To address these problems, we start by analyzing the signal part of 5G out-of-band signals falling into the BD B1 signal band, conduct a detailed analysis of the mixed signal regime and frequency planning, and design a hybrid receiver architecture compatible with both signals, and propose an SC-PMF-FFT fast capture algorithm based on strong correlation, which takes advantage of the strong correlation of signals broadcast on the BD B1 frequency point from B1I to B1C, and reuses the structure of the CDMA system signal capture algorithm to complete the fast capture of 5G signals using an OFDM system. The experiments show that the method can capture the BeiDou B1 signal with a sensitivity of −154 dBm and a whole constellation capture time of no more than 40 ms with the inlet power of the 5G signal not exceeding −45 dBw.
... The ground-based cellular radio communication (especially 5G) base station network could be used as an important national PNT infrastructure. The cellular radio base station network could provide PNT services for users within the coverage (Liu et al., 2020;Zhang et al., 2022), and at least can be an important compensation for major domestic PNT infrastructures. ...
Satellite navigation systems are vulnerable. To guarantee the positioning, navigation and timing (PNT) safety of core infrastructure, it is necessary to establish a secure PNT system with hybrid physical principles. In this paper, the augmentations of the BeiDou satellite system (BDS) itself are analysed, namely augmentations through the BDS inter-satellite link, BDS geostationary orbit (GEO) and inclined geostationary orbit (IGSO) satellites, and BDS PNT services supported by low earth orbit (LEO) satellites. Then, taking BDS as the core component, the comprehensive PNT infrastructure seamlessly covering deep space and deep ocean is described, consisting of the deep space PNT constellation, the sea-floor PNT sonar beacon network, and the ground-based low frequency and very low frequency (VLF) long wave radio stations. Moreover, the key technologies of resilient PNT application matching comprehensive PNT and various autonomous perception PNT information are discussed, such as resilient PNT sensor integration, the resilient PNT functional model and the resilient stochastic model. As a future development direction, the key factors of intelligent PNT services are analysed, including the intelligent perception of PNT application scenes, the intelligent optimization of PNT functional and stochastic models and the intelligent fusion of multisource PNT information.
... The results of the simulated four occlusion scenarios exhibited that the introduction of 5G ranging signals could greatly improve the overall positioning continuity of the Federation Filter. Zhang et al. [41] used a device-to-device communication mode to combine the 5G observations based on time of arrival (TOA) and received signal strength methods with the GNSS observations for 3D positioning and experimentally demonstrated that this algorithm performs markedly better than the GNSS pseudorange positioning in both static and dynamic positioning, with more than 50% improvement in accuracy. Bai et al. [42] proposed a model that can fuse the GNSS and 5G observations at different rates based on the high-rate characteristics of 5G observations. ...
Global Navigation Satellite System provides real-time and all-weather positioning with high accuracy. Under a good observational environment, short-baseline real-time kinematic (RTK) can provide centimeter-level positioning results. However, RTK without model correction of ionospheric delay will significantly reduce the positioning accuracy, and cannot achieve fast and high-precision positioning when the baseline is too long or heavily occluded. Therefore, we proposed a combined RTK/fifth-generation (5G) mobile communication technology positioning model by combining global positioning system-RTK with the 5G time of arrival observations to improve the positioning accuracy under medium and long baselines. Experimental validation and analysis were conducted based on the measured data of different baseline lengths. Results revealed that the combined RTK/5G positioning model markedly improved the positioning performance in both static and dynamic modes under medium- and long-distance baselines. In particular, the RTK/5G model can also achieve good positioning results in conditions where some satellites are occluded. The combined RTK/5G positioning model is important for achieving high accuracy and real-time and continuous positioning in complex environments.
... the communication range and offer the positions based on the national coordinate reference. On the other hand, the positioning signals can also be transmitted and received directly between the requesting nodes and the other MUs with known positions based on the device-to-device (D2D) links, referred to as the D2D cooperative positioning (Zhang et al., 2022). To be specific, as one of the key technologies in the 5G network, D2D communication allows the direct links between the MUs in proximity, which prompts the cooperative positioning with highaccuracy and low-delay positioning signals. ...
The integration of BeiDou System (BDS) and the fifth generation (5G) system is expected to provide positioning services with high accuracy and reliability. In particular, as an important technique in the 5G system, device-to-device (D2D) communication enables the cooperative positioning for the mobile users (MUs) to offer a large number of redundant measurements, where the received signal strength (RSS) measurement can be exploited due to its easy access and cost-efficiency. However, the RSS measurements cannot be accurately modelled to reflect the propagation distances. In this paper, a robust BDS/5G integrated positioning scheme based on the resilient observation model is proposed. Specifically, the extended Kalman filter (EKF) is exploited to recursively integrate the BDS pseudorange and RSS measurements to estimate the unknown position parameters. We establish a resilient observation model based on the signal propagation model in the 5G network, through which the errors in the RSS measurements are compensated for by the BDS pseudorange measurements. Moreover, the effects of the abnormal errors in both kinds of the measurements are controlled by the robust estimation through automatically adjusting the weights of the measurements. Numerical results show that the proposed resilient observation model can correct part of the errors in the RSS measurements and results in higher positioning accuracy compared to the positioning based on the RSS measurements or the direct integration of both the BDS pseudorange and RSS measurements in different scenarios. The proposed algorithm also outperforms the positioning based on the BDS pseudorange measurements when the visible satellites are not sufficient.
This study proposes a model using 5G time-of-arrival data to assist global navigation satellite system precise point positioning ambiguity resolution. Specifically, the model addresses the problem of PPP requiring a long convergence time in partially satellite-occluded GNSS environments, such as urban canyons. First, we apply the ionosphere-free PPP model to estimate uncalibrated phase delays. Next, we combine real 5G data with GNSS data to determine whether introducing 5G observations will decrease the convergence time of the PPP solution. Experimental results reveal that the 5G-assisted PPP model can effectively improve the convergence efficiency of the float solution, lower the fixed time, and achieve greater positional reliability. Notably, the combination of GPS, BDS, and 5G with a sampling interval of 1 s obtains a fixed solution in an average of 1.12 min. Moreover, 5G-assisted GNSS positioning effectively compensates for partial satellite occlusion, optimizes the PDOP value, and speeds up ambiguity fixing. The introduction of three and more 5G base stations helps to obtain fixed solutions within 9 min when it is difficult to obtain fixed solutions relying only on GNSS. Our findings have important implications for improving the widespread applicability and effectiveness of satellite-based navigation systems in light of increasing urbanization and the rise of signal-occluding environments.
Smartphone positioning methods relying solely on GNSS are susceptible to significant errors in urban environments due to challenging observation conditions. To enhance position accuracy, this paper introduces a novel 5G observation model based on unit vectors and evaluates its performance using several user locations and precision observation data. The results demonstrate that the unit vector method, compared to the traditional angle of departure approach, effectively reduces the nonlinearity of the observation model, leading to a substantial improvement in the 5G system’s positioning accuracy. Furthermore, we conduct experiments to investigate the impact of the geometric distribution of 5G base station height on positioning accuracy. The results reveal a significant influence, highlighting the importance of considering base station height in the positioning process. In the urban environment, introducing 5G base station angle observations as an aid to GNSS significantly enhances the reliability of smartphone positioning, achieving positioning errors of less than one meter. Notably, this approach outperforms the introduction of 5G distance observations, providing valuable insights for the development of seamless indoor and outdoor positioning systems in the future.
This letter presents a novel mobility-aware device-to-device (D2D) cooperative positioning scheme for dynamic nodes. We employ the Gauss-Markov mobility model to represent and simulate the movement of mobile nodes. Initially, we create a Euclidean distance tensor (EDT) by combining Euclidean distance matrices (EDMs) collected at various time stamps. The non-line of sight (NLoS) conditions in global navigation satellite system (GNSS)-Denied environments lead to missing data in EDM which results in inaccurate positioning of D2D nodes. To address this issue, we utilize the high accuracy low rank tensor completion (HaLRTC) algorithm to effectively fill in the missing entries within the EDMs for each time stamp. Subsequently, we utilize multidimensional scaling (MDS) to derive the relative positions of the nodes. While the locations of the anchor nodes remain fixed, we employ Procrustes analysis (PA) to determine the global positions of the unknown nodes. Simulation results demonstrate that our proposed approach achieves a localization error of 0.2017 m with a sparsity level of 90%, along with a ranging error rate of 20%, thus offering high accuracy.
