Achievable Throughput Analysis of Opportunistic Spectrum Access in Cognitive Radio Networks With Energy Harvesting

Bae, Yun Han; Baek, Jung Woo

doi:10.1109/tcomm.2016.2533485

Cited by 46 publications

(19 citation statements)

References 23 publications

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“…In this context, many studies examined harvesting in CRNs [14,17,[21][22][23][24][25]. Park et al [17] proposed an efficient spectrum sensing strategy to maximize the total throughput of SUs under energy and collision constraints.…”

Section: Introductionmentioning

confidence: 99%

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Throughput Optimization of Multichannel Allocation Mechanism under Interference Constraint for Hybrid Overlay/underlay Cognitive Radio Networks with Energy Harvesting

Karaca

2020

Electronics

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By harvesting energy from ambient radio frequency (RF) signals, significant progress has been achieved in wireless networks self-maintaining their life cycles. Motivated by this and improved spectrum reuse by combined use of overlay/underlay modes of cognitive radio networks (CRNs), this paper proposes a novel multi-channel (m-channel) allocation performance maximization algorithm for low-power mobiles. CRNs, called secondary transmitters (STs), can harvest energy from RF signals by nearby active primary transmitters (PTs). In the proposed scheme, PTs and STs are distributed as independent homogeneous Poisson point processes and contact their receivers at fixed distances. Each PT contains a guard zone to protect its intended receiver from ST interference, and provides RF energy to STs located in its harvesting zone. Prioritization of STs during opportunistic allocation of channels is critical as properties like energy level and harvesting capability improve channel distribution performance. A novel metric is proposed that prioritizes STs based on initial energy levels, harvesting capability, and number of channels through which they can transmit. For comparison, three algorithms were considered: a greedy mechanism for m-channel allocation of hybrid CRNs without harvesting, the proposed m-channel allocation schemes based on maximum independent sets (MIS), and the proposed metric of hybrid CRNs with harvesting capability. The simulations show that the proposed m-channel allocation method based on MIS outperforms the greedy algorithm. The proposed m-channel allocation using the proposed metric on hybrid CRNs with energy harvesting ability produced the best performance of the three methods, proving the superiority of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

“…Pratibha et al [24] updated the homogeneous Poisson point processes (HPPPs) to construct a decentralized channel-selection mechanism to improve the throughput of SUs in multi-band CRNs. Bae et al [25] examined how sensing probability, access probability, and energy queue capacity affect the manageable throughput of a multi-user CRN.…”

Section: Introductionmentioning

confidence: 99%

Throughput Optimization of Multichannel Allocation Mechanism under Interference Constraint for Hybrid Overlay/underlay Cognitive Radio Networks with Energy Harvesting

Karaca

2020

Electronics

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“…To realize a green, sustainable and secure HCRN, tradeoff studies among the detection performance, achievable throughput, energy utilization, and security are critical problems that need to be addressed. Towards this end, HCRNs with energy harvesting (EH) spectrum sensors ( [8], [9]) are considered, which enhance both spectrum efficiency and energy efficiency ( [10], [11], [12], [13]).…”

Section: Introductionmentioning

confidence: 99%

Sensing-Throughput Tradeoff for Superior Selective Reporting-Based Spectrum Sensing in Energy Harvesting HCRNs

Kishore

Gurugopinath

Muhaidat

et al. 2019

IEEE Trans. Cogn. Commun. Netw.

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In this paper, we investigate the performance of conventional cooperative sensing (CCS) and superior selective reporting (SSR)-based cooperative sensing in an energy harvestingenabled heterogeneous cognitive radio network (HCRN). In particular, we derive expressions for the achievable throughput of both schemes and formulate nonlinear integer programming problems, in order to find the throughput-optimal set of spectrum sensors scheduled to sense a particular channel, given primary user (PU) interference and energy harvesting constraints. Furthermore, we present novel solutions for the underlying optimization problems based on the cross-entropy (CE) method, and compare the performance with exhaustive search and greedy algorithms. Finally, we discuss the tradeoff between the average achievable throughput of the SSR and CCS schemes, and highlight the regime where the SSR scheme outperforms the CCS scheme. Notably, we show that there is an inherent tradeoff between the channel available time and the detection accuracy. Our numerical results show that, as the number of spectrum sensors increases, the channel available time gains a higher priority in an HCRN, as opposed to detection accuracy.

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“…Some recent studies [ 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ] have focused on exploiting and investigating the performance of wireless communication systems with energy harvesting. Time resources, sensing parameters and power resources have become very important issues on optimizing the system performance.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the finite-horizon partially observable Markov decision process (POMDP), they derived the dynamic sensing access policy. The authors in [ 22 ] aimed to investigate the impact of sensing probability, access probability, and energy queue capacity on the maximum achievable throughput. They proposed a two-step opportunistic spectrum access for CRN with energy harvesting and derived the sensing probability.…”

Section: Introductionmentioning

confidence: 99%

Optimal Time Assignment Policy for Maximizing Throughput in Cognitive Sensor Network with Energy Harvesting

Chen

2018

Sensors

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A cognitive sensor network with energy harvesting (EH-CSN) is a promising paradigm to address the issues both in spectrum efficiency and in energy efficiency. The cognitive sensors (CSs) equipped with energy harvesting devices are assumed to operate in a harvesting-sensing-transmission mode and permitted to access the idle licensed frequency bands without causing any harmful jamming to the primary user. By identifying the time fractions of harvesting, sensing, and transmission, we can discuss some design considerations for the EH-CSN. In the meantime, considering the possibility that the primary user may reoccupy the idle channel during the CS’s data transmission duration, we formulate an optimization problem to maximize the average throughput of EH-CSN under a collision constraint and an energy constraint. After deriving the lower and upper bounds of the time fraction for energy harvesting, the uniqueness and existence of the optimal time fraction set have been proved. Finally, our theoretical analysis is also verified through numerical simulations.

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Achievable Throughput Analysis of Opportunistic Spectrum Access in Cognitive Radio Networks With Energy Harvesting

Cited by 46 publications

References 23 publications

Throughput Optimization of Multichannel Allocation Mechanism under Interference Constraint for Hybrid Overlay/underlay Cognitive Radio Networks with Energy Harvesting

Throughput Optimization of Multichannel Allocation Mechanism under Interference Constraint for Hybrid Overlay/underlay Cognitive Radio Networks with Energy Harvesting

Sensing-Throughput Tradeoff for Superior Selective Reporting-Based Spectrum Sensing in Energy Harvesting HCRNs

Optimal Time Assignment Policy for Maximizing Throughput in Cognitive Sensor Network with Energy Harvesting

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