Full-Duplex Cooperative Sensing for Spectrum-Heterogeneous Cognitive Radio Networks

Liu, Peng; Qi, Wangdong; Yuan, En; Li, Wei; Zhao, Yuexin

doi:10.3390/s17081773

Cited by 8 publications

(9 citation statements)

References 35 publications

(73 reference statements)

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“…Authors divided the novel opportunistic capacity model into two modules to reduce the computational complexity and solve them using the Lagrangian dual method. In [24], authors developed a supportive sensing method, which is based on the pairwise secondary user transmitter and receiver. Authors presented the detailed protocol description to illustrate the working of the projected framework.…”

Section: Spectrum Sensingmentioning

confidence: 99%

Primary User Traffic Pattern Based Opportunistic Spectrum Handoff in Cognitive Radio Networks

et al. 2020

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Through the expeditious expansion of the wireless network, the unlicensed bandwidth-based devices are growing substantially as compared to the present vacant bandwidth. Cognitive radio networks present a proficient solution to the spectrum shortage diminution hitch by allowing the usage of the vacant part of the spectrum that is not currently in use of the Primary User licensed bandwidth to the secondary user or cognitive radio user. Spectrum management procedure in cognitive radio network comprises of spectrum sharing, sensing and handoff. Spectrum handoff plays a vital role in spectrum management and primarily focuses on single handoff strategies. This paper presents a primary user traffic pattern-based opportunistic spectrum handoff (PUTPOSH) approach to use in the cognitive radio networks. PUTPOSH permits a secondary user to sense the arrival of a primary user and use an opportunistic handoff scheme. The opportunistic handoff scheme firstly detects the arrival of the primary users by energy detection sensing and secondly, it allows a cognitive radio user to decide whether to do handoff or not contingent upon the overall service time to reduce the unused handoffs. The handoffs can either be reactive or proactive based on the arrival rate of the primary user. The simulation results show that the presented PUTPOSH approach (a) minimizes the number of handoffs and the overall service time, and (b) maintains the channel utilization and throughput of the system at a maximal point.

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Section: Spectrum Sensingmentioning

confidence: 99%

Primary User Traffic Pattern Based Opportunistic Spectrum Handoff in Cognitive Radio Networks

et al. 2020

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“…Such limitations in HD-CRNs result in the inefficient use of system resources. To consider the above limitations, in-band full duplex (FD) radios have been proposed [18,19,20]. The FD-CRNs can simultaneously perform sensing and transmission in each time slot.…”

Section: Introductionmentioning

confidence: 99%

Spatial–Temporal Sensing and Utilization in Full Duplex Spectrum-Heterogeneous Cognitive Radio Networks for the Internet of Things

Khalid

2019

Sensors

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The continuous growth of interconnected devices in the Internet of Things (IoT) presents a challenge in terms of network resources. Cognitive radio (CR) is a promising technology thatcan address the IoT spectral demands by enabling an opportunistic spectrum access (OSA) scheme. The application of full duplex (FD) radios in spectrum sensing enables secondary users (SUs) to perform sensing and transmission simultaneously, and improves the utilization of the spectrum. However, random and dense distributions of FD-enabled SU transmitters (FD-SU TXs) with sensing capabilities in small-cell CR-IoT environments poses new challenges, and creates heterogeneous environments with different spectral opportunities. In this paper, we propose a spatial and temporal spectral-hole sensing framework for FD-SU TXs deployed in CR-IoT spectrum-heterogeneous environment. Incorporating the proposed sensing model, we present the analytical formulation and an evaluation of a utilization of spectrum (UoS) scheme for FD-SU TXs present at different spatialpositions. The numerical results are evaluated under different network and sensing parameters to examine the sensitivities of different parameters. It is demonstrated that self-interference, primary user activity level, and the sensing outcomes in spatial and temporal domains have a significant influence on the utilization performance of spectrum.

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“…Spectrum sensing is a key link of cognitive radio and the perceived performance will directly affect the performance of the whole cognitive radio system [1]. At present, the commonly-used spectrum sensing technologies can be divided into three categories: single-user spectrum sensing, distributed collaborative spectrum sensing, and centralized collaborative spectrum sensing.…”

Section: Introductionmentioning

confidence: 99%

Malicious Cognitive User Identification Algorithm in Centralized Spectrum Sensing System

2017

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Collaborative spectral sensing can fuse the perceived results of multiple cognitive users, and thus will improve the accuracy of perceived results. However, the multi-source features of the perceived results result in security problems in the system. When there is a high probability of a malicious user attack, the traditional algorithm can correctly identify the malicious users. However, when the probability of attack by malicious users is reduced, it is almost impossible to use the traditional algorithm to correctly distinguish between honest users and malicious users, which greatly reduces the perceived performance. To address the problem above, based on the β function and the feedback iteration mathematical method, this paper proposes a malicious user identification algorithm under multi-channel cooperative conditions (β-MIAMC), which involves comprehensively assessing the cognitive user's performance on multiple sub-channels to identify the malicious user. Simulation results show under the same attack probability, compared with the traditional algorithm, the β-MIAMC algorithm can more accurately identify the malicious users, reducing the false alarm probability of malicious users by more than 20%. When the attack probability is greater than 7%, the proposed algorithm can identify the malicious users with 100% certainty.

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Full-Duplex Cooperative Sensing for Spectrum-Heterogeneous Cognitive Radio Networks

Cited by 8 publications

References 35 publications

Primary User Traffic Pattern Based Opportunistic Spectrum Handoff in Cognitive Radio Networks

Primary User Traffic Pattern Based Opportunistic Spectrum Handoff in Cognitive Radio Networks

Spatial–Temporal Sensing and Utilization in Full Duplex Spectrum-Heterogeneous Cognitive Radio Networks for the Internet of Things

Malicious Cognitive User Identification Algorithm in Centralized Spectrum Sensing System

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