Optimization of relay selection and ergodic capacity in cognitive radio sensor networks with wireless energy harvesting

Wang, Ying; Lin, Wenxuan; Sun, Ruijin; Huo, Yongjia

doi:10.1016/j.pmcj.2015.06.001

Cited by 17 publications

(12 citation statements)

References 30 publications

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“…g In addition to the convexity of problem (8), we can trivially verify that the slater's condition [14] for problem (8) holds. Therefore, we can achieve the optimal solution to problem (8) by solving its dual problem.…”

Section: Solution Methodsmentioning

confidence: 94%

“…In the interweave paradigm, secondary users (SUs) first harvest energy and then opportunistically access the licensed spectrum when primary users (PUs) are detected as inactive [4]- [7]. In the overlay paradigm, SUs use the harvested energy from the PU signal to forward the data of both PUs and SUs, provided that perfect cooperations between PUs and SUs [8]- [10] are assumed. In the underlay paradigm, SUs harvest energy from the RF signal of PUs or other SUs, and transmit with the harvested energy provided the interference to PUs is below a tolerable threshold [11]- [12].…”

Section: Introductionmentioning

confidence: 99%

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Harvesting-Throughput Tradeoff for CDMA-Based Underlay Cognitive Radio Networks With Wireless Energy Harvesting

Zheng

Liang

Huang

2018

IEEE Systems Journal

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Abstract-This paper considers a green cognitive radio network wherein each secondary user (SU) is solely powered by an energy harvester which extracts energy from RF signals of a primary user transmitter. Each SU operates in a harvesting-transmitting fashion periodically. In each period, all SUs first harvest energy for a fixed duration and then transmit data using the harvested energy to one access point for the rest of the period in the code-division multiple access method. Considering the intrinsic harvestingthroughput tradeoff, we jointly optimize the harvesting time and transmit powers of SUs to maximize the sum throughput of the network, subject to the primary interference constraint and the energy causality constraint. Despite of the nonconvex nature of the formulated optimization problem, we find an equivalent but convex substitution to the original problem. Then, we propose a dual-decomposition-based solution method to solve the problem. Simulations finally demonstrate the efficiency of this paper.

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Section: Solution Methodsmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Harvesting-Throughput Tradeoff for CDMA-Based Underlay Cognitive Radio Networks With Wireless Energy Harvesting

Zheng

Liang

Huang

2018

IEEE Systems Journal

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“…In [17], [18], throughput maximization is studied for the case that one SU harvests energy from ambient RF signals, serves as the relay for PUs, and communicates with another SU. After extending one SU to multiple SUs, relay selection to maximize throughput or sum-throughput is investigated in [19], [20], wherein SUs harvest from PUs or a hybrid access point (H-AP). In [21], sum-throughput maximization is studied for overlay EH-CRNs, wherein first H-AP performs WET for multiple SUs as well as information transmission for PUs, and then collects data from SUs.…”

Section: Related Workmentioning

confidence: 99%

End-to-End Throughput Maximization for Underlay Multi-Hop Cognitive Radio Networks With RF Energy Harvesting

Zheng

Liang

et al. 2017

IEEE Trans. Wireless Commun.

149

141

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Abstract-This paper studies a green paradigm for the underlay coexistence of primary users (PUs) and secondary users (SUs) in energy harvesting cognitive radio networks (EH-CRNs), wherein battery-free SUs capture both the spectrum and the energy of PUs to enhance spectrum efficiency and green energy utilization. To lower the transmit powers of SUs, we employ multi-hop transmission with time division multiple access, by which SUs first harvest energy from the RF signals of PUs, and then, transmit data in the allocated time concurrently with PUs, all in the licensed spectrum. In this way, the available transmit energy of each SU mainly depends on the harvested energy before the turn to transmit, namely energy causality. Meanwhile, the transmit powers of SUs must be strictly controlled to protect PUs from harmful interference. Thus, subject to the energy causality constraint and the interference power constraint, we study the end-to-end throughput maximization problem for optimal time and power allocation. To solve this nonconvex problem, we first equivalently transform it into a convex optimization problem and then propose the joint optimal time and power allocation (JOTPA) algorithm that iteratively solves a series of feasibility problems until convergence. Extensive simulations evaluate the performance of EH-CRNs with JOTPA in three typical deployment scenarios and validate the superiority of JOTPA by making comparisons with two other resource allocation algorithms.

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“…According to the coexistence paradigm, the existing works on RF-CRNs can be classified into three categories, namely, interweave [7]- [9], overlay [11]- [13] and underlay [14]- [16]. In the interweave paradigm, secondary users (SUs) first harvest energy and then opportunistically access the licensed spectrum when primary users (PUs) are detected as inactive [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

“…In the interweave paradigm, secondary users (SUs) first harvest energy and then opportunistically access the licensed spectrum when primary users (PUs) are detected as inactive [7]- [9]. In the overlay paradigm, SUs use the harvested energy from the PU signal to forward the data of both PUs and SUs, provided that perfect cooperations between PUs and SUs [11]- [13] are assumed. In the underlay paradigm, SUs harvest energy from the RF signal of PUs or other SUs, and transmit with the harvested energy provided the interference to PUs is below a tolerable threshold [14]- [16].…”

Section: Introductionmentioning

confidence: 99%

Resource Allocation for an Underlay Wireless Powered Cognitive Radio

Song¹,

Zheng²

2017

2017 IEEE 85th Vehicular Technology Conference (VTC Spring)

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Abstract-This paper investigates an underlay cognitive radio (CR) that extracts energy from radio-frequency signals of one primary user. We assume that both the wireless energy harvesting and the secondary transmission processes of the CR suffer Rayleigh block fading. Considering the intrinsic harvesting-transmitting tradeoff, we optimize the harvesting time and transmit power of the CR to minimize the outage probability of the secondary transmission, subject to the primary interference and the energy causality constraints. Numerical evaluation validates the correctness of this work.

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Optimization of relay selection and ergodic capacity in cognitive radio sensor networks with wireless energy harvesting

Cited by 17 publications

References 30 publications

Harvesting-Throughput Tradeoff for CDMA-Based Underlay Cognitive Radio Networks With Wireless Energy Harvesting

Harvesting-Throughput Tradeoff for CDMA-Based Underlay Cognitive Radio Networks With Wireless Energy Harvesting

End-to-End Throughput Maximization for Underlay Multi-Hop Cognitive Radio Networks With RF Energy Harvesting

Resource Allocation for an Underlay Wireless Powered Cognitive Radio

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