e-space
Manchester Metropolitan University's Research Repository

    Securing radio resources allocation with deep reinforcement learning for IoE services in next-generation wireless networks

    Peng, Yuhuai, Xue, Xiaojing, Bashir, Ali Kashif ORCID logoORCID: https://orcid.org/0000-0001-7595-2522, Zhu, Xiaogang, Al-Otaibi, Yasser D, Tariq, Usman and Yu, Keping (2022) Securing radio resources allocation with deep reinforcement learning for IoE services in next-generation wireless networks. IEEE Transactions on Network Science and Engineering, 9 (5). pp. 2991-3003. ISSN 2327-4697

    [img]
    Preview
    Accepted Version
    Download (8MB) | Preview

    Abstract

    The next generation wireless network (NGWN) is undergoing an unprecedented revolution, in which trillions of machines, people, and objects are interconnected to realize the Internet of Everything (IoE). with the emergence of IoE services such as virtual reality, augmented reality, and industrial 5G, the scarcity of radio resources becomes more serious. Moreover, there are hidden dangers of untrusted terminals accessing the system and illegally manipulating interconnected devices. To tackle these challenges, this paper proposes a securing radio resources allocation scheme with Deep Reinforcement Learning for IoE services in NGWN. First, the solution uses a BP neural network based on multi-feature optimized Firefly Algorithm (FA) for spectrum prediction, thereby improving the prediction accuracy and avoiding interference between unauthorized and authorized users with efficient radio utilization. Then, a spectrum sensing method based on deep reinforcement learning is proposed to identify the untrusted users in system while fusing the sensing results, to enhance the security of the cooperative process and the detection accuracy of spectrum holes. Extensive simulation results show that the proposal is superior to the traditional solutions in terms of prediction accuracy, spectrum utilization and energy consumption, and is suitable for deployment in future wireless systems.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    57Downloads
    6 month trend
    33Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Actions (login required)

    View Item View Item