Design an Optimum Energy Harvesting Model for Bidirectional Cognitive Radio Networks (original) (raw)
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Optimum energy harvesting model for bidirectional cognitive radio networks
EURASIP Journal on Wireless Communications and Networking, 2021
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 h...
Throughput of a Cognitive Radio Network With Energy-Harvesting Based on Primary User Signal
IEEE Wireless Communications Letters, 2016
In this paper, we analyze an energy-harvesting based Cognitive Radio (CR) system. The CR system harvests energy from the radio frequency (RF) signal of primary user (PU) during sensing time as well as the transmission time of a detection cycle if PU is present. The CR accesses the spectrum band of PU opportunistically using the energy harvested over the frames with PU present, while maintaining a quality of service (QoS) constraint on PU in terms of a collision probability. An optimal sensing time is found which maximizes the harvested energy. The performance is investigated in terms of harvested energy, outage probability and throughput of the network. Novel analytical expressions for average harvested energy and average throughput are developed under such a scenario which are validated by simulation.
Residual Energy of Energy Harvesting Cognitive Radio Networks
International Journal of Engineering and Advanced Technology, 2019
This paper analyzes cooperative spectrum sensing with energy harvesting using power splitting mode of operation simultaneously. Secondary users (SU) will harvests RF energy from primary user (PU) throughout the durations of sensing and transmission. The main aim of this paper is to analyze the residual energy of SU with power splitting ratio, number of samples, number of SUs and probability of detection. Mathematical expressions of energy consumption, harvested energy and residual energy are developed. The simulation results of residual energy with different parameters are verified and have proved that residual energy of SUs is increased with increase in power splitting ratio, number of SUs, number of samples of SU for sensing and probability of detection
Throughput of an Energy Harvesting Cognitive Radio Network based on Prediction of Primary User
IEEE Transactions on Vehicular Technology, 2017
In this paper, a novel prediction based cooperative spectrum sensing scheme is investigated on the performance of an energy harvesting cognitive radio (CR) network. The spectrum sensing scheme is redesigned to protect the quality of service (QoS) of primary user (PU) and to improve the utilization of spectrum holes. The decision about the PU spectrum status and energy harvesting (RF and non-RF) of a CR node are based on prediction as well as sensing at individual CR level. We consider simultaneous spectrum sensing and energy harvesting scenario through the incorporation of an energy splitting device. A CR harvests from non-RF resources if both the decisions (decision of prediction and decision of spectrum sensing) do not match or if both the decisions match in favour of the absence of PU. On contrary, it harvests from RF resources while both the decisions match in favour of the presence of PU. A CR node transmits only if both decisions indicate the absence of PU. A CR user opportunistically uses the PU spectrum for its transmission purpose under a collision constraint. The collision constraint gives an extra protection to the QoS of PU on re-arrival of PU. Novel analytical expressions for detection performance, harvested energy and network throughput are developed. The impact of prediction and other network parameters such as number of detection frames, number of cooperative CR user, splitting parameter, collision probability on throughput performance is investigated. Improvement in spectrum reuse and energy penalty during harvesting is indicated. Impact of noise power estimation on the sensing performance is also studied.
Cognitive radio network with continuous energy-harvesting
International Journal of Communication Systems, 2016
In this paper, the performance of a cooperative cognitive radio (CR) network is investigated under continuous energy harvesting scenario. A CR node harvests energy from both the sources: non-radio frequency (RF) signal (ambient sources) or from RF signal (primary user signal). It harvests from non-RF signal during sensing time of its detection cycle, and from both the sources, RF signal and non-RF signal, during transmission time as per sensing decision. Several novel analytical expressions are developed to indicate the harvested energy, energy reward, energy cost in a detection frame, and throughput. The performance of the CR network is investigated to maximize the throughput considering energy causality constraints and collision constraints. Analytical results are validated through extensive simulation results.
Hybrid Energy Harvesting Scheme for Cognitive Radio Network
2021
Cognitive radio networks are becoming increasingly popular these days because of their propensity to tackle spectrum shortage problem so efficiently through dynamic spectrum access. The cognitive radios are battery operated devices and require continuous spectrum monitoring for the opportunistic use of the spectrum. Thus, the performance of such radios is limited by the battery life. To overcome this bottleneck, a hybrid energy harvesting scheme is proposed in this paper. The proposed scheme harvest energy from RF energy from PU as well as SU on detecting their presence and absence from the channel. The proposed algorithm compares the harvested energy with desired transmission power. If the harvested energy is less than desired transmission power, external energy source is used to meet the deficit. The numerical simulated results are presented and compared with the conventional scheme to validate the proposed scheme. Keywords— Cognitive radio network, Energy harvesting.
2022
Background and Objectives: In an energy harvesting cognitive radio network, both energy efficiency and spectrum efficiency can be improved, simultaneously. In this paper, we consider an energy harvesting-based multiantenna cognitive radio network to execute cooperative spectrum sensing, data transmission and RF energy harvesting by secondary transmitter from PU' signal and the ambient noise, simultaneously. Methods: In his paper, two novel models called Joint Power allocation and Energy Harvesting by Time switching and Antennas splitting (JPEHTA) and Joint Power allocation and Continuous Energy Harvesting (JPCEH) are proposed. We formulate the joint optimization problems of the sensing time, detection threshold, energy harvesting time, number of cooperative antennas for sensing and energy harvesting as well as power allocation for each antenna in both proposed models. The aim is for enhancing both the spectral and the energy efficiencies under constraints on the probabilities of global detection and false alarm, energy harvesting and transmission power budget. Then, the considered multi-variable problem is solved by using two convex-based iterative proposed algorithms having less computational complexity compared to baseline approaches to achieve the optimal parameters and goals of the problem. Results: The results present insights about the impact of the sensing time, detection threshold, power allocation and the number of antennas on the energy and spectrum efficiencies of cognitive radio network with an energy harvesting capability. Conclusion: Simulation results have shown that the proposed schemes outperform the structures that have not optimized all the parameters considered in this paper, jointly or schemes in which single-antenna SU are participated in spectrum sensing, energy harvesting and data transmitting.
Impact of Primary Networks on the Performance of Energy Harvesting Cognitive Radio Networks
IET Communications, 2016
In this paper, we investigate the effect of of the primary network on the secondary network when harvesting energy in cognitive radio in the presence of multiple power beacons and multiple secondary transmitters. In particular, the influence of the primary transmitter's transmit power on the energy harvesting secondary network is examined by studying two scenarios of primary transmitter's location, i.e., the primary transmitter's location is near to the secondary network, where the primary transmitter can interfere the secondary receiver, and the primary transmitter's location is far from the secondary network, where the secondary receiver is free from the interference. In addition, the peak interference constraint at the primary receiver is also considered. In the scenario where the primary transmitter locates near to the secondary network, although secondary transmitter can be benefit from the harvested energy from the primary transmitter, the interference caused by the primary transmitter suppresses the secondary network performance. Meanwhile, in both scenarios, despite the fact that the transmit power of the secondary transmitter can be improved by the support of powerful power beacons, the peak interference constraint at the primary receiver limits this advantage. In addition, the deployment of multiple power beacons and multiple secondary transmitters can improve the performance of the secondary network. The analytical expressions of the outage probability of the secondary network in the two scenarios are also provided and verified by numerical simulations.
Survey on energy harvesting cognitive radio networks
2015
Energy harvesting network (EHN) is a trending topic among the recent researches. This substantial attention is due to the limitations, operational cost and risks of the conventional power suppliers, such as fossil fuel and batteries. Moreover, EHN are expected to enhance energy efficiency by harvesting energy of RF and renewable sources. In contemporary research works, EHN is applied to CR technology. This energy harvesting cognitive radio network (EHCRN) is expected to utilize both energy and electromagnetic spectrum efficiently. However, EH-CRN is facing enormous challenges related to technical design. Some of these challenges are reviewed in recent surveys. However, other challenges such as optimizing the network throughput and EH-CRN implementation models were not the focus of these researches. Therefore, the aim of this survey is to review EH-CRN research works by focusing the survey perspective on maximizing the network throughput and the implementation models.