Integrated Cooperative Spectrum Sensing and Access Control for Cognitive Industrial Internet of Things

Liu, Xin; Jia, Min; Zhou, Mu; Wang, Bin; Durrani, T.S.

doi:10.1109/jiot.2021.3137408

Cited by 16 publications

(11 citation statements)

References 28 publications

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“…Moreover, with the increase of p d or k, we deduce that the collision probability P s is more likely to decrease with the number of mini-slots n based on (19).…”

mentioning

confidence: 83%

“…The probability of a false alarm and the probability of detection are two important indicators of spectrum-sensing accuracy. The low probability of a false alarm improves the spectrumaccess efficiency, while the high probability of detection reduces the interference with the PU [19]. By exploiting the spatial diversity, cooperative SUs obtain better sensing accuracy by CSS than a single SU.…”

Section: Introductionmentioning

confidence: 99%

“…When k ∈ [(1 − p d )(n + 1) + 1, n], the right-hand side of (18) depends on p d and k. Specifically, in (19), the summation of x ∈ [0, (1…”

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confidence: 99%

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Trade-Offs among Sensing, Reporting, and Transmission in Cooperative CRNs

Liu

Zheng

2022

Sensors

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Cooperative spectrum sensing (CSS) has been verified as an effective approach to improve the sensing performances of cognitive radio networks (CRNs). Compared with existing works that commonly consider fusion with fixed inputs and neglect the duration of the reporting period in the design, we novelly investigate a fundamental trade-off among three periods of CSS: sensing, reporting, and transmission periods, and evaluate the impact of the fusion rule with a varying number of local sensing results. To be specific, the sensing time could be traded for additional mini-slots to report more local sensing results for fusion, or it could be traded for longer transmission time. In the CRNs with a given durations of sensing/reporting/transmission periods, we, respectively, formulate the throughput and collision probability and optimize the throughput under the collision constraint. The theoretical results show that, in the specific value intervals of the sensing parameters, the collision constraint provides an upper bound of the number of mini-slots in the reporting period or a lower bound of the sensing duration. We provide the approach to the maximum throughput in some cases.Finally, numerical results are presented to validate theoretical results.

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“…Moreover, with the increase of p d or k, we deduce that the collision probability P s is more likely to decrease with the number of mini-slots n based on (19).…”

mentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

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Trade-Offs among Sensing, Reporting, and Transmission in Cooperative CRNs

Liu

Zheng

2022

Sensors

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“…Finally, the simulation results reveal the effectiveness of the CRACIIoT scheme [3]. Xin Liu et al develop the Integrated Spectrum Sensing for CIIoT (ISSCIIoT) scheme for the integrated cooperative spectrum sensing and access control processes [4]. In this scheme, the main goal is to maximize the total throughput of CIIoT system by jointly optimizing sensing time, the number of sensing nodes and the transmit power for each CIIoT device.…”

Section: Related Workmentioning

confidence: 99%

“…However, this spectrum band is also adopted by other communication networks, such as ZigBee, WiFi, Bluetooth, etc. Therefore, it has become very crowded; the scarcity of spectrum resources is a key technical bottleneck to restrict the development of IIoT technology [1]- [2], [4].…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent Learning and Bargaining Scheme for Cooperative Spectrum Sharing Process

Kim

2023

IEEE Access

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Recently, the lack of spectrum resources has become a key technical bottleneck to develop the Industrial Internet of Things (IIoT). Based on cognitive radio technology, the cognitive IIoT (CIIoT) paradigm can improve spectrum utilization via opportunistically accessing the idle spectrum bands. In this study, a novel cooperative spectrum sharing scheme is presented for the CIIoT system platform. The main challenge of our scheme is to effectively share the limited spectrum resource via cooperative sensing and dynamic accessing techniques. To achieve a mutually desirable solution for different CIIoT devices, we design a learning game model using the ideas of multi-agent reinforcement learning (MARL) and the negotiated aspirations bargaining solution (NABS). In the learning mechanism, individual CIIoT devices adaptively select their cooperative sensing policy according to the MARL model. In the bargaining mechanism, the available spectrum resource is dynamically shared through the NABS, which is obtained based on the devices' selected sensing policy. By investigating the contribution of MARL to game theory, the proposed scheme can effectively guide intelligent CIIoT devices toward a socially optimal outcome. Numerical simulation results demonstrate that the normalized device payoff, CIIoT system throughput and device fairness of our approach are better than those of existing benchmark protocols. Finally, we present the key challenges and future direction of our research in the CIIoT system operations.

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Optimal sensing duration and threshold selection approach in cognitive radio networks with cooperative spectrum sensing

Vinod,

Sharma,

Singh

2024

Int J Communication

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SummaryPerfect detection of unused/underutilized frequency band of the primary user (PU) in the cognitive radio communication systems is an essential component for its efficient utilization by the secondary/cognitive user (CU) without any interference. In the cooperative spectrum sensing scenario, the presence or absence of PU is determined by analyzing the decisions of each CU engaged in the collaboration. In this paper, we have emphasized on the significance of spectrum sensing duration in the optimal threshold selection approach in the cooperative spectrum sensing scenarios for a range of the received PU signal signal‐to‐noise ratio (SNR) from low to high values. The sensing duration parameter is taken as ts = 2.5 ms in the higher SNR environment, whereas in the lower SNR environment when the optimal threshold condition fails, ts is kept dynamic to satisfy minimum target values of sensing performance parameters. We have computed the spectrum sensing performance parameters and throughput using the same approach and compared the results with those obtained from the constant false‐alarm rate (CFAR), constant detection rate (CDR), and minimized error probability (MEP) threshold selection approaches. The spectrum sensing performance computed by the proposed approach is significantly improved as compared with the other reported approaches. At SNR = −24 dB, global probability of false alarm Qf = 0.002 and global probability of detection Qd = 0.999 are achieved. However, the throughput is relatively less for low SNR values.

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Integrated Cooperative Spectrum Sensing and Access Control for Cognitive Industrial Internet of Things

Cited by 16 publications

References 28 publications

Trade-Offs among Sensing, Reporting, and Transmission in Cooperative CRNs

Trade-Offs among Sensing, Reporting, and Transmission in Cooperative CRNs

Multi-Agent Learning and Bargaining Scheme for Cooperative Spectrum Sharing Process

Optimal sensing duration and threshold selection approach in cognitive radio networks with cooperative spectrum sensing

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