An Optimal Policy for Hybrid Channel Access in Cognitive Radio Networks With Energy Harvesting

Tayel, Ahmed F.; Rabia, Sherif I.; El‐Malek, Ahmed H. Abd; Abdelrazek, Amr M.

doi:10.1109/tvt.2020.3008671

Cited by 15 publications

(14 citation statements)

References 40 publications

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“…Recently, RF EH in CSN has become the object of extensive research [10][11][12][13][14][15][16][17][18]. In [10], a two-phase decoded-andforward (DF) relay model was constructed by employing adaptive PS at the ST node; the outage probability and throughput were analysed.…”

Section: Introductionmentioning

confidence: 99%

“…In [12], the SU's EE maximization problem was formulated under energy causality and the PU's QoS requirement constraint; a joint time and power allocation scheme was proposed in the overlay network. In [13], the SU accessed the PU's channel in a hybrid interweave/underlay mode using the time division multiple access (TDMA) technique to maximize the SU's throughput. In [14], asymptotic closed-form expressions for the spectrum efficiency (SE) and outage probability were derived at the constraints of the interference temperature and residual energy harvested from PT in an underlay network.…”

Section: Introductionmentioning

confidence: 99%

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Energy Efficiency Analysis in Modified GoF Spectrum Sensing-Based AF Relay Cooperative Cognitive Sensor Network with Energy Harvesting

Gao

2021

Security and Communication Networks

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In this paper, we propose a joint sensing duration and transmission power allocation scheme to maximize the energy efficiency (EE) of the secondary user (SU) in a cooperative cognitive sensor network (CSN). At the initial time slot of the frame, the secondary transmitter (ST) performs energy harvesting (EH) and spectrum sensing simultaneously using power splitting (PS) protocol. The modified goodness of fit (GoF) spectrum sensing algorithm is employed to detect the licensed spectrum, which is not sensitive to an inaccurate noise power estimate. Based on the imperfect sensing results, the ST will act as an amplify-and-forward (AF) relay and assist in transmission of the primary user (PU) or transmit its own data. The SU’s EE maximization problem is constructed under the constraints of meeting energy causality, sensing reliability, and PU’s quality of service (QoS) requirement. Since the SU’s EE function is a nonconvex problem and difficult to solve, we transform the original problem into a tractable convex one with the aid of Dinkelbach’s method and convex optimization technique by applying a nonlinear fractional programming. The closed-form expression of the ST’s transmission power is also derived through Karush-Kuhn-Tucker (KKT) and gradient method. Simulation results show that our scheme is superior to the existing schemes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Energy Efficiency Analysis in Modified GoF Spectrum Sensing-Based AF Relay Cooperative Cognitive Sensor Network with Energy Harvesting

Gao

2021

Security and Communication Networks

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“…3) The performance of the hybrid multi-channel access scheme in the RF-CRN is evaluated in terms of the transmit power allocations, energy efficiency, the data transmission rate, spectrum sensing duration, and the effects of the inter-cluster and intra-cluster interference on the QoS of the network. Simulation results show that there can be improved energy harvesting in the [4] Throughput [5], [7], [11] Throughput [8], [9], [10] Throughput [13] Throughput [14], [16] Throughput [12] Throughput [15] Throughput [6] Throughput [17] Throughput [18], [19] Throughput [20], [21] Energy Efficiency [22] Energy Efficiency [23], [24] Energy Efficiency This paper Energy Efficiency TDMA based RF-CRN for enhanced active probability and hence, improved achievable throughput of SUs if the multi-user scenario can be exploited. Nevertheless, a trade-off exists between harvested energy and the achievable throughput of each SU, thus an optimum number of SU exists where the average throughput of each SU is maximized.…”

Section: B Main Contributionsmentioning

confidence: 92%

“…In [17], through monotocity analysis, Zheng et al formulated the problem to determine the optimal detection threshold that maximizes the secondary user throughput. Authors in [18], [19] investigated an hybrid channel access cognitive radio in a network consisting one PU and multiple SUs. More actions are added to the options of the decision making and energy-based restrictions are applied before taking any action instead of assuming that energy is always sufficient for sensing and transmission.…”

Section: A Related Workmentioning

confidence: 99%

Resource Allocation in Multi-Cluster Cognitive Radio Networks With Energy Harvesting for Hybrid Multi-Channel Access

Olawole

Takawira

2023

IEEE Access

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Cognitive radio and energy harvesting techniques have been able to provide insight for solutions to the inefficiency in spectrum utilization and the effects of the limited storage capacity of energy batteries. Nevertheless, the requirement for interference constraint for primary user (PU) protection, the quality of service (QoS) requirements of the SUs, and the low power density of the ambient electromagnetic waves have restricted the performance of the radio frequency powered cognitive radio networks (RF-CRNs) in terms of the achievable data rate for specific energy budget or sufficient energy budget for target data rate. We are therefore motivated to investigate a radio frequency powered cognitive radio (RF-CR) with the capacity for improved achievable throughput and energy harvesting. Our model consists of multiple PUs and SUs coexisting in a practical overlapping clustered network. In each time frame for the adopted time division multiple access (TDMA) technique, SUs can exploit the multi-user benefit to harvest energy from both the PU and SUs transmissions for improved active probability. Therefore, taken into consideration the heterogeneity of each SUs in terms of their signal-to-noise (SNR), the energy harvesting rates and the inter-and intra-cluster interference, the problem is formulated into a fractional nonlinear optimization to determine the sensing duration, and power allocations that maximize the average energy efficiency of the RF-CRN subject, to constraints on energy causality, and PU protection. The performance of the proposed hybrid multi-channel access scheme is studied in terms of the trade-off between the total achievable throughput by the secondary users and the interference generated among others. Simulation results show that a trade-off exists between achieving optimal spectral efficiency and energy efficiency and, the optimal transmit power therefore depends on the primary design objective. Results equally show that the proposed hybrid multi-channel access scheme outperforms the existing scheme in literature.INDEX TERMS Energy efficiency, hybrid multi-channel access, multi-cluster network, radio frequency powered cognitive radio network (RF-CRN), resource allocation (RA).

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“…In previous studies on cognitive wireless-powered communication (see [7][8][9][10][11] and reference therein), it was considered that the IoT node firstly harvests energy from the primary signal and subsequently uses the harvested energy to transmit signal by accessing the spectrum of the primary user via active radios (AR). In AR, the IoT node needs to generate the carrier signal and modulate its information on the carrier signal.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Resource Allocation in Cognitive Wireless-Powered Hybrid Active-Passive Communications

Luo

Ning

2022

Wireless Communications and Mobile Computing

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Integrating hybrid active-passive communications into cognitive radio can achieve a spectrum- and energy-efficiency information transmission, while the resource allocation has not been well studied particularly for the network with multiple secondary users (also termed as the Internet of Things (IoT) users). In this article, we formulate an optimization problem to maximize the energy efficiency of all the IoT nodes in a cognitive wireless-powered hybrid active-passive communication network by taking the interference from the IoT node to the primary link, the energy causality constraint, and the minimum throughput constraint per IoT node. By using the Dinkelbach method and introducing auxiliary variables, we devise an iterative algorithm to optimally solve the formulated problem. Computer simulations are provided to validate the quick convergence of the iterative algorithm and the advantages of the proposed scheme in terms of the energy efficiency.

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An Optimal Policy for Hybrid Channel Access in Cognitive Radio Networks With Energy Harvesting

Cited by 15 publications

References 40 publications

Energy Efficiency Analysis in Modified GoF Spectrum Sensing-Based AF Relay Cooperative Cognitive Sensor Network with Energy Harvesting

Energy Efficiency Analysis in Modified GoF Spectrum Sensing-Based AF Relay Cooperative Cognitive Sensor Network with Energy Harvesting

Resource Allocation in Multi-Cluster Cognitive Radio Networks With Energy Harvesting for Hybrid Multi-Channel Access

Energy-Efficient Resource Allocation in Cognitive Wireless-Powered Hybrid Active-Passive Communications

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