Cooperative spectrum sharing-based relaying protocols with wireless energy harvesting cognitive user

2018 ◽  
Vol 12 (7) ◽  
pp. 838-847 ◽  
Author(s):  
Tarun Kalluri ◽  
Mansi Peer ◽  
Vivek Ashok Bohara ◽  
Daniel B. daCosta ◽  
Ugo S. Dias
Keyword(s):  
Energy Harvesting ◽  
Spectrum Sharing ◽  
Relaying Protocols ◽  
Cooperative Spectrum Sharing ◽  
Wireless Energy Harvesting ◽  
Cognitive User

scholarly journals Subcarrier Allocation Based Cooperative Spectrum Sharing with Wireless Energy Harvesting in OFDM Relaying Networks

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2663
Author(s):  
Dan Huang ◽  
Mengshu Hou ◽  
Weidang Lu
Keyword(s):  
Energy Harvesting ◽  
Spectrum Sharing ◽  
Transmission Rate ◽  
Relay Node ◽  
Cognitive System ◽  
Subcarrier Allocation ◽  
Cooperative Spectrum Sharing ◽  
Simulation Results ◽  
Relaying Networks ◽  
Wireless Energy Harvesting

In this paper, we propose subcarrier allocation based cooperative spectrum sharing protocol for OFDM relaying networks with wireless energy harvesting. In the proposed protocol, the cognitive relay node utilizes different subcarriers to forward the primary information to obtain the spectrum access for the cognitive system transmission. The primary system consists of two parts, a primary transmitter (PT) and primary receiver (PR), and cognitive system includes a cognitive source node (CSN), cognitive destination node (CDN) and cognitive relay node (CRN). In the first phase, CRN splits a fraction of the power received from the PT and CSN transmission to decode information, while the remaining power is used for energy harvesting. Then CRN uses disjoint subcarriers to forward the signals of PT and CSN by utilizing the harvested energy in the second phase. Three parameters which consist of power splitting ratio, power allocation and subcarriers allocation are optimized in our algorithm to maximize the cognitive transmission rate with the constraint of primary target transmission rate. Numerical and simulation results are shown to give useful insights into the proposed cooperative spectrum sharing protocol, and we also found that various system parameters have a great effect for the simulation results.

scholarly journals Spectrum Sharing Network With Wireless Energy Harvesting at Finite Blocklength Regime

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 60198-60205
Author(s):  
Baogang Li ◽  
Ruonan Dong ◽  
Binyang Yan ◽  
Wei Zhao
Keyword(s):  
Energy Harvesting ◽  
Spectrum Sharing ◽  
Wireless Energy Harvesting

scholarly journals Relaying Protocols for Wireless Energy Harvesting and Information Processing

2013 ◽  
Vol 12 (7) ◽  
pp. 3622-3636 ◽  
Author(s):  
Ali A. Nasir ◽  
Xiangyun Zhou ◽  
Salman Durrani ◽  
Rodney A. Kennedy
Keyword(s):  
Information Processing ◽  
Energy Harvesting ◽  
Relaying Protocols ◽  
Wireless Energy Harvesting

scholarly journals Secure Information Transmissions in Wireless-Powered Cognitive Radio Networks for Internet of Medical Things

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Kun Tang ◽  
Wenjuan Tang ◽  
Entao Luo ◽  
Zhiyuan Tan ◽  
Weizhi Meng ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Spectrum Sharing ◽  
Medical Information ◽  
Transmission Rate ◽  
Sensitive Information ◽  
Secondary System ◽  
Secure Information ◽  
Internet Of Medical Things ◽  
Wireless Energy Harvesting

In this paper, we consider the issue of the secure transmissions for the cognitive radio-based Internet of Medical Things (IoMT) with wireless energy harvesting. In these systems, a primary transmitter (PT) will transmit its sensitive medical information to a primary receiver (PR) by a multi-antenna-based secondary transmitter (ST), where we consider that a potential eavesdropper may listen to the PT’s sensitive information. Meanwhile, the ST also transmits its own information concurrently by utilizing spectrum sharing. We aim to propose a novel scheme for jointly designing the optimal parameters, i.e., energy harvesting (EH) time ratio and secure beamforming vectors, for maximizing the primary secrecy transmission rate while guaranteeing secondary transmission requirement. For solving the nonconvex optimization problem, we transfer the problem into convex optimization form by adopting the semidefinite relaxation (SDR) method and Charnes–Cooper transformation technique. Then, the optimal secure beamforming vectors and energy harvesting duration can be obtained easily by utilizing the CVX tools. According to the simulation results of secrecy transmission rate, i.e., secrecy capacity, we can observe that the proposed protocol for the considered system model can effectively promote the primary secrecy transmission rate when compared with traditional zero-forcing (ZF) scheme, while ensuring the transmission rate of the secondary system.

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