Total Throughput Maximization of Cooperative Cognitive Radio Networks With Energy Harvesting

Zheng, Kechen; Li, Xiaoying; Zhu, Yi-hua; Chi, Kaikai; Liu, Kangqi

doi:10.1109/twc.2019.2946813

Cited by 38 publications

(32 citation statements)

References 28 publications

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“…The EH-CRNs have been widely studied since the issues of spectrum and energy scarcities can be alleviated [8][9][10][11]. In EH-CRNs, the RF signals radiated by PTs could be viewed as energy resources to secondary networks, and STs with EH functionality are able to convert the energy of RF signals into electrical energy.…”

Section: Introductionmentioning

confidence: 99%

Throughput maximisation for multi‐channel energy harvesting cognitive radio networks with hybrid overlay/underlay transmission

et al. 2022

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This paper focuses on the issue of joint time and power allocation in multi‐channel energy harvesting CR networks (EH‐CRNs), where the multi‐antenna secondary transmitter (ST) opportunistically accesses the licensed subchannels by a hybrid overlay/underlay transmission approach. To improve spectrum efficiency and energy efficiency of the EH‐CRNs, the ST scavenges energy from the radio‐frequency signal radiated by the primary transmitter, and exploits the harvested energy for data transmission through subchannels of different states in overlay/underlay mode simultaneously. Moreover, under the interference power constraint, energy constraint, and maximum power constraint, the secondary throughput is improved by optimising the allocation of subchannels, the time scheduling between energy harvesting and data transmission, and the power allocation of the ST among different subchannels. A subchannel allocation scheme with low time complexity is proposed, and the secondary throughput optimisation problem is formulated with respect to the time scheduling and power allocation of the ST. Then it is proved the problem is convex, and the problem is solved by a proposed joint time and power allocation algorithm. Numerical results show that the proposed scheme has an advantage of secondary throughput over the other schemes. Finally, the impacts of key relevant factors on the secondary throughput are explored.

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Section: Introductionmentioning

confidence: 99%

Throughput maximisation for multi‐channel energy harvesting cognitive radio networks with hybrid overlay/underlay transmission

et al. 2022

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“…CR technology allows the secondary users (SUs) to access the spectrum licensed to the primary users (PUs), based on the premise that the quality of service (QoS) requirement of the PUs must be guaranteed [2,3]. In the CR networks, underlay and overlay are two main schemes that the SUs share the spectrum with the PUs [4,5]. In the underlay paradigm, the SUs transmit concurrently in the same spectrum with the PUs, if the interference caused by the SUs to the PUs is below a given threshold.…”

Section: Introduction 1cr Network With Rf Energy-harvestingmentioning

confidence: 99%

Secrecy Performance Maximization for Underlay CR Networks with an Energy Harvesting Jammer

Sun

Zhang

Chi

2021

Sensors

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This paper investigates the secrecy communication in an underlay cognitive radio (CR) networks with one primary user (PU) as well as multiple PUs, where the radio frequency (RF) energy-harvesting secondary user (SU) transmits the confidential information to the destination in the presence of a potential eavesdropper. We introduce a RF energy-harvesting secondary jammer (SJ) to secure the SU transmissions. The system works in time slots, where each time slot is divided into the energy transfer (ET) phase and the information transfer (IT) phase. In ET phase, the SU and SJ capture energy from the PU transmissions; in the IT phase, the SU uses the harvested energy to transmit information to the destination without causing the harmful interference to the PU transmissions, while the SJ utilizes the captured energy to generate jamming signals to the eavesdropper to secure the SU transmissions. We aim to maximize the secrecy rate for SU transmissionsby jointly optimizing the time allocation between ET phase and IT phase and the transmit power allocation at the SU and SJ. We first formulate the secrecy rate maximization as non-convex optimization problems. Then, we propose efficient nested form algorithms for the non-convex problems. In the outer layer, we obtain the optimal time allocation by the one dimension search method. In the inner layer, we obtain the optimal transmit power allocation by the DC programming, where the Lagrange duality method is employed to solve the convex approximation problem. Simulation results verify that the proposed schemes essentially improve the secrecy rate of the secondary network as compared to the benchmark schemes.

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“…The gradually-matured energy harvesting technology promises sustainable operation for wireless sensor networks (WSNs), in which energy sources include radio frequency (RF) signals [1][2][3], sunlight [4], vibration [5] etc. Energy-harvesting WSNs (EH-WSNs) with a single energy source usually exhibit some limitations.…”

Section: Introductionmentioning

confidence: 99%

Slot‐hitting ratio‐based TDMA schedule for hybrid energy‐harvesting wireless sensor networks

Gong

Zheng

et al. 2020

IET Communications

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Total Throughput Maximization of Cooperative Cognitive Radio Networks With Energy Harvesting

Cited by 38 publications

References 28 publications

Throughput maximisation for multi‐channel energy harvesting cognitive radio networks with hybrid overlay/underlay transmission

Throughput maximisation for multi‐channel energy harvesting cognitive radio networks with hybrid overlay/underlay transmission

Secrecy Performance Maximization for Underlay CR Networks with an Energy Harvesting Jammer

Slot‐hitting ratio‐based TDMA schedule for hybrid energy‐harvesting wireless sensor networks

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