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  • 1
    Online Resource
    Online Resource
    Energy-efficient power control strategy of the delay tolerable service based on the reinforcement learning
    Elsevier BV ; 2023
    In:  Computer Communications Vol. 210 ( 2023-10), p. 102-115
    Details
    In: Computer Communications, Elsevier BV, Vol. 210 ( 2023-10), p. 102-115
    Type of Medium: Online Resource
    ISSN: 0140-3664
    URL: Article
    DOI: 10.1016/j.comcom.2023.07.034
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 1478742-8
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  • 2
    Online Resource
    Online Resource
    Outlier-Resistant Localization for Smart Cities: Low-Rank Approximation-Based Approaches
    Hindawi Limited ; 2022
    In:  Scientific Programming Vol. 2022 ( 2022-1-31), p. 1-13
    Details
    In: Scientific Programming, Hindawi Limited, Vol. 2022 ( 2022-1-31), p. 1-13
    Abstract: For smart cities, location-based services (LBSs) are indispensable; however, the urban environment is typically a multipath channel and achieving high accuracy localization is challenging, especially in GNSS-denied environments. It is already known that there are two key factors that constrain IoT localization performance, namely, the presence of outliers in the inter-node ranging data and the difficulty to guarantee that ranging is carried out between all nodes, which means that we are dealing with an incomplete Euclidean distance matrix (EDM) contaminated with outliers. In this paper, we propose a robust localization framework, termed low-rank approximation-based localization (LRAbL). LRAbL enables network localization in a stepwise manner using partially observed EDMs that contain coarse noise (outliers). Specifically, the working process of LRAbL can be divided into three stages: the preprocessing of the observed EDM, aiming to eliminate outliers with large values, the use of low-rank approximation means to obtain the complete EDM, and finally the application of non-classical MDS to calculate the coordinates of the nodes in the network. To confirm the applicability of the proposed framework, extensive numerical experiments were conducted, which indicated that LRAbL was still able to achieve satisfactory localization results when the network links were sparse (only about 1/4 of the entries can be observed) and contained a certain percentage of large value outliers. In summary, our work provides a solution worthy of consideration for location-based services in the future Internet of Things.
    Type of Medium: Online Resource
    ISSN: 1875-919X , 1058-9244
    URL: Article
    DOI: 10.1155/2022/6847850
    RVK:
    SA 7860
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2070004-0
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  • 3
    Online Resource
    Online Resource
    Spectrum Efficient Resource Allocation of NOMA Downlink System With MMSE Receiver
    Institute of Electrical and Electronics Engineers (IEEE) ; 2023
    In:  IEEE Access Vol. 11 ( 2023), p. 27414-27425
    Details
    In: IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), Vol. 11 ( 2023), p. 27414-27425
    Type of Medium: Online Resource
    ISSN: 2169-3536
    URL: Article
    DOI: 10.1109/ACCESS.2023.3258451
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2023
    detail.hit.zdb_id: 2687964-5
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  • 4
    Online Resource
    Online Resource
    An Indoor Localization Method Based on the Combination of Indoor Map Information and Inertial Navigation with Cascade Filter
    Hindawi Limited ; 2021
    In:  Journal of Sensors Vol. 2021 ( 2021-12-23), p. 1-11
    Details
    In: Journal of Sensors, Hindawi Limited, Vol. 2021 ( 2021-12-23), p. 1-11
    Abstract: The specific objective of this study is to propose a low-cost indoor navigation framework with nonbasic equipment by combining inertial sensors and indoor map messages. The proposed pedestrian navigation framework consists of a lower filter and an upper filter. In the lower filter which is designed based on the Kalman filter, the adaptive zero velocity detection algorithm is used to detect the zero velocity interval at different motion speeds, and then, zero velocity update is applied to rectify the inertial navigation solutions’ errors. In the upper filter which is designed based on the nonrecursive Bayesian filter, the map matching method with nonrecursive Bayesian filter is adopted to fuse the map prior information and the lower filter estimation results to correct the errors of navigation. The position estimation presented in this study achieves an average position error of 0.53 m compared to the ZUPT-aided inertial navigation system (INS) method under different motion states. The proposed pedestrian navigation algorithm achieves an average position error of 0.54 m as compared to the ZUPT-aided INS method among the different tested distances. The proposed framework simplifies the indoor positioning system under multiple motion speed conditions by ensuring the accuracy and stability property. The effectiveness and accuracy of the proposed framework are experimentally verified in various real-world scenarios.
    Type of Medium: Online Resource
    ISSN: 1687-7268 , 1687-725X
    URL: Article
    DOI: 10.1155/2021/7621393
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2397931-8
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  • 5
    Online Resource
    Online Resource
    Localization of IoT networks: An empirical bayesian approach
    IOP Publishing ; 2020
    In:  Journal of Physics: Conference Series Vol. 1629, No. 1 ( 2020-09-01), p. 012003-
    Details
    In: Journal of Physics: Conference Series, IOP Publishing, Vol. 1629, No. 1 ( 2020-09-01), p. 012003-
    Abstract: Location information is an important component of big data, so it has attracted many researchers’ attention to obtain the location of the target based on edge computing. However, in the actual application scenario, due to the influence of non-line-of-sight (NLOS) propagation, relative localization of anchorless networks in complex scenarios is a challenging issue. In this paper, we propose a robust localization framework based on a distributed architecture, which is suitable for the edge computing environment. The proposed framework consists of three steps, firstly, using hierarchical clustering method, the network is divided into several sub-clusters with a small number of nodes. Secondly, in each sub-cluster, outlier detection and low-rank matrix completion algorithms are used to complete the Euclidian distance matrix (EDM), furthermore, MDS is used to calculate the relative coordinates. In the last step, the relative coordinates of all sub-clusters are transformed and stitched to realize the whole network localization. In order to verify the effectiveness of the proposed framework, we carry out a large number of numerical simulations, the results show that our framework can effectively eliminate the outliers caused by NLOS and improve the localization performance in a complex environment.
    Type of Medium: Online Resource
    ISSN: 1742-6588 , 1742-6596
    URL: Article
    DOI: 10.1088/1742-6596/1629/1/012003
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2020
    detail.hit.zdb_id: 2166409-2
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  • 6
    Online Resource
    Online Resource
    High-Performance Computational Recognition of Communication Signals Based on Bispectral Quadratic Feature Model
    Hindawi Limited ; 2022
    In:  Computational Intelligence and Neuroscience Vol. 2022 ( 2022-4-26), p. 1-12
    Details
    In: Computational Intelligence and Neuroscience, Hindawi Limited, Vol. 2022 ( 2022-4-26), p. 1-12
    Abstract: In response to the problems in the signal identification of radiation sources during the communication process, the bispectral quadratic feature model is applied to the identification algorithm for communication signals. According to the signal eigenvalues obtained from the bispectrum of the diagonal slices in the radiation source signals, the eigenvalues of the bispectrum diagonal slices can be extended from the frequency domain to the complex plane through the chirp-z operation in this paper, and the relevant data are obtained based on the bispectrum quadratic feature model of the signals by using the separation rules corresponding to the extended Babbitt distance. The bispectral quadratic feature model method is used to establish a sparse observation model, and the communication signal processing problem can be transformed into an estimation problem of signal motion parameters through the construction of a parametric database. At the same time, the high-resolution distance of communication signals is tested, and the communication signals are estimated by using the variational inference method. Finally, practical cases are analyzed, and the results indicate that the algorithm proposed in this paper can be used to identify different types of communication signals in accordance with simulated and measured data in the processing of communication signals in various environments, which has the certain anti-interference capacity to noise, can improve the identification rate of communication signals, and has verified the effectiveness and practicality of the algorithm proposed in this paper.
    Type of Medium: Online Resource
    ISSN: 1687-5273 , 1687-5265
    URL: Article
    DOI: 10.1155/2022/2773492
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2388208-6
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