Maximizing Energy Efficiency in Hybrid Overlay-Underlay Cognitive Radio Networks Based on Energy Harvesting-Cooperative Spectrum Sensing

Liu, Yan; Qin, Xizhong; Huang, Yan; Tang, Li; Fu, Jinjuan

doi:10.3390/en15082803

Cited by 9 publications

(5 citation statements)

References 29 publications

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“…Various research papers have already been written on the hybrid spectrum access technique, covering it from a variety of methods and perspectives. A portion of these works is reviewed here [11][12][13][14][15]. The success of the hybrid spectrum scheme heavily depends on its ability to accurately detect the presence or absence of a PU.…”

Section: Hybrid Spectrum Access (Has)mentioning

confidence: 99%

Design and Development of Hybrid Spectrum Access Technique for CR-IoT Network

lakhian¹

2023

Mesopotamian Journal of Computer Science

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The radio spectrum is an underutilized natural resource with significant untapped potential. The rapid proliferation of Internet of Things (IoT) devices is driving a dramatic increase in radio spectrum demand. These devices can utilize cognitive radio (CR) technology to access the bandwidth left unused by licensed spectrum users, also known as primary users (PUs), to meet end users spectrum requirements efficiently. However, because PUs are given priority, CR-enabled Internet of Things (CR-IoT) devices, also known as secondary users (SU), must frequently communicate with one another in an opportunistic manner or under stringent power constraints. This can complicate CR-IoT device communication, render it unstable, and restrict its throughput. This paper proposes a hybrid spectrum access algorithm that combines underlay and interweave spectrum access methods to address this issue. When a PU is detected, under the proposed scheme, CR-IoT devices utilize underlay spectrum access. In contrast, when no PU is detected, CR-IoT devices employ interweave spectrum access. In addition, a proposed iterative algorithm permits CR-IoT devices to adapt their sensing thresholds, and sensing time based on the Signal-to-Noise ratio (SNR) received from Pus to strike a balance between achievable throughput and fairness among PUs and CR-IoT devices in extremely noisy channel. Simulation results demonstrate that the throughput for CR-IoT devices increases by 28% in proposed scheme when compared to the conventional spectrum access schemes.

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Section: Hybrid Spectrum Access (Has)mentioning

confidence: 99%

Design and Development of Hybrid Spectrum Access Technique for CR-IoT Network

lakhian¹

2023

Mesopotamian Journal of Computer Science

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“…[10], on the other hand, suggests using advanced cognitive radios that can sense and transmit simultaneously. Some researchers, such as those in [11] and [12], rely on machine learning to predict the likelihood of idle licensed bands, thereby reducing the sensing time by only sensing a few channels. However, these solutions have high computational overhead and may be too expensive for battery-constrained IoT devices.…”

Section: Related Work and Main Contributionsmentioning

confidence: 99%

Enhancing Hybrid Spectrum Access in CR-IoT Networks: Reducing Sensing Time in Low SNR Environments

Hlapisi

2023

Mesopotamian Journal of Computer Science

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The current utilization of the licensed spectrum band is not optimal. the abundance of Internet of Things (IoT) gadgets could lead to congestion in the unlicensed spectrum band. A potential solution is to integrate cognitive radios into IoT devices, specifically by developing CR-IoT (cognitive-radio-enabled IoT) devices that leverage the hybrid spectrum access (HSA) technique to access the licensed spectrum band and employ energy detectors for spectrum sensing. While HSA can enable high data throughput for CR-IoT networks, environments with low signal-to-noise ratio (SNR) may experience reduced performance. Particularly, in low SNR environments with SNR values ranging from -20dB to -24dB, the high level of noise uncertainty can cause the energy detector to spend more time sensing, which results in a significant reduction in transmission time and overall throughput. In this study, a novel approach is presented to address the challenge of noise uncertainties on the energy detector by implementing an adaptive sensing threshold. The simulation outcomes reveal that the proposed technique can significantly improve the throughput in scenarios characterized by low signal-to-noise ratio (SNR), with a maximum enhancement of up to 28%. This innovative approach can pave the way for more robust and efficient energy detectors in the presence of noise uncertainties .

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“…In [60], authors discussed the spectrum detection as a main operation in CR where the channel corruptions by SUs identify the PUs presence. This accurate detection was achieved by CSS that exploits the SUs spatial diversity and it was based on the energy sensing in which the performance under noise or intrusion were not satisfied [61].…”

Section: Literature Surveymentioning

confidence: 99%

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

Kumar,

Sharanya

2023

ijmst

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During the last decade, Cognitive Radio Network (CRN) technology has been a significant advance in addressing the ever-increasing spectrum demand. As the number of licensed and unlicensed users in a network rises to complete a certain activity, the information exchange between various types of traffic becomes more complex and difficult. Congestion in CRN is also caused by the conflict among several users for channel access (PUs and SUs). In a very crowded network, many applications perform badly owing to packet collisions and, as a result, packet loss before significant buffer queue building. This circumstance is aggravated by an increase in network users. Congestion control is a vital and essential aspect of the present research issue in communication networks. Several recent reviews in the literature indicate that the congestion issue in the CRN has not been thoroughly studied. Thus, effective and efficient congestion control strategies are sought to optimize network resource usage and management. To prevent congestion, it is crucial for CRN to do research on the creation of an efficient congestion management system. This will improve the network's resource consumption and performance. "Performance improvement via efficient spectrum management through optimum resource management and congestion control in the CRN by mitigating different threats" is the primary target of this project. This research also focused on enhancing performance by addressing security issues in an IoT-based CRN environment. This study provides a comprehensive review of several similar studies and their limitations, which may be used to formulate a new research target.

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Maximizing Energy Efficiency in Hybrid Overlay-Underlay Cognitive Radio Networks Based on Energy Harvesting-Cooperative Spectrum Sensing

Cited by 9 publications

References 29 publications

Design and Development of Hybrid Spectrum Access Technique for CR-IoT Network

Design and Development of Hybrid Spectrum Access Technique for CR-IoT Network

Enhancing Hybrid Spectrum Access in CR-IoT Networks: Reducing Sensing Time in Low SNR Environments

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

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