Throughput Maximization of Hybrid Access in Multi-Class Cognitive Radio Networks With Energy Harvesting

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

doi:10.1109/tcomm.2021.3059862

Cited by 25 publications

(8 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

“…Hybrid interweave/underlay access scheme is investigated in [17]- [19]. In [17], through monotocity analysis, Zheng et al formulated the problem to determine the optimal detection threshold that maximizes the secondary user throughput.…”

Section: A Related Workmentioning

confidence: 99%

“…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%

See 2 more Smart Citations

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

Olawole

Takawira

2023

IEEE Access

View full text Add to dashboard Cite

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).

show abstract

Section: B Main Contributionsmentioning

confidence: 92%

Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

See 1 more Smart Citation

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

Olawole

Takawira

2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Besides, the authors derived the closed-form expressions of outage probability of SU network and introduced an optimization problem to reduce the SU outage probability for transmission power. Novel hybrid underlay channel model in secondary SU network with EH capability was studied in Tayel et al [15]. Besides, closed-form expression for energy transmission and outage probability for the underlay model in Rayleigh fading channel was derived in their works of primary users (PU) based on smart sensing capability [8].…”

Section: Time Switching Techniquementioning

confidence: 99%

Optimum energy harvesting model for bidirectional cognitive radio networks

Hasan¹,

Chowdhury²,

Ahmed³

et al. 2021

J Wireless Com Network

View full text Add to dashboard Cite

Wireless devices’ energy efficiency and spectrum shortage problem has become a key concern worldwide as the number of wireless devices increases at an unparalleled speed. Wireless energy harvesting technique from traditional radio frequency signals is suitable for extending mobile devices’ battery life. This paper investigates a cognitive radio network model where primary users have their specific licensed band, and secondary users equipped with necessary hardware required for energy harvesting can use the licensed band of the primary user by smart sensing capability. Analytical expressions for considered network metrics, namely data rate, outage probability, and energy efficiency, are derived for uplink and downlink scenarios. In addition, optimal transmission power and energy harvesting power are derived for maximum energy efficiency in downlink and uplink scenarios. Numerical results show that outage probability improves high transmission power in the downlink scenario and high harvested power in the uplink scenario. Finally, the result shows that energy efficiency improves using optimum transmission power and energy harvesting power for downlink and uplink scenarios.

show abstract

“…With the development of wireless communication technology, 5G communication network is faced with the problem of short spectrum resources and large energy consumption. Therefore, cognitive radio technology [1][2][3] and energy harvesting technology [4][5][6][7] have received extensive attention. Secondary users (SUs) choose to cooperate with primary users (PUs) to seek opportunities for more effective data transmission [8,9].…”

Section: Introductionmentioning

confidence: 99%

Optimal Cooperation Scheme Based on Improved Artificial Bee Colony for Energy Harvesting Cognitive Network

Lin

Wang

et al. 2021

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

The cognitive relay wireless communication system is lack of the specific cooperation needs between primary user (PU) and secondary user (SU). In this paper, we propose an optimal cooperative scheme of energy harvesting cognitive relay based on SU's willingness. The SU chooses to carry small packets of data according to their own needs to cooperate with PU. The maximum throughput equation of SU is derived from the proposed optimal cooperation scheme. The improved artificial bee colony (IABC) algorithm is used to solve SU's throughput equation optimization problem. The simulation results show that the IABC algorithm has better convergence than the original algorithm. The system throughput has been improved obviously.

show abstract

Throughput Maximization of Hybrid Access in Multi-Class Cognitive Radio Networks With Energy Harvesting

Cited by 25 publications

References 34 publications

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

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

Optimum energy harvesting model for bidirectional cognitive radio networks

Optimal Cooperation Scheme Based on Improved Artificial Bee Colony for Energy Harvesting Cognitive Network

Contact Info

Product

Resources

About