In this letter, we consider the harvested-energy fairness problem in cognitive multicast systems with simultaneous wireless information and power transfer. In the cognitive multicast system, a cognitive transmitter with multi-antenna sends the same information to cognitive users in the presence of licensed users, and cognitive users can decode information and harvest energy with a power-splitting structure. The harvested-energy fairness problem is formulated and solved by using two proposed algorithms, which are based on semidefinite relaxation with majorization-minimization method, and sequential parametric convex approximation with feasible point pursuit technique, respectively. Finally, the performances of the proposed solutions and baseline schemes are verified by simulation results.
Pham-Viet TUAN
University of Ulsan,Hue University
Insoo KOO
University of Ulsan
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Pham-Viet TUAN, Insoo KOO, "Simultaneous Wireless Information and Power Transfer Solutions for Energy-Harvesting Fairness in Cognitive Multicast Systems" in IEICE TRANSACTIONS on Fundamentals,
vol. E101-A, no. 11, pp. 1988-1992, November 2018, doi: 10.1587/transfun.E101.A.1988.
Abstract: In this letter, we consider the harvested-energy fairness problem in cognitive multicast systems with simultaneous wireless information and power transfer. In the cognitive multicast system, a cognitive transmitter with multi-antenna sends the same information to cognitive users in the presence of licensed users, and cognitive users can decode information and harvest energy with a power-splitting structure. The harvested-energy fairness problem is formulated and solved by using two proposed algorithms, which are based on semidefinite relaxation with majorization-minimization method, and sequential parametric convex approximation with feasible point pursuit technique, respectively. Finally, the performances of the proposed solutions and baseline schemes are verified by simulation results.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E101.A.1988/_p
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@ARTICLE{e101-a_11_1988,
author={Pham-Viet TUAN, Insoo KOO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Simultaneous Wireless Information and Power Transfer Solutions for Energy-Harvesting Fairness in Cognitive Multicast Systems},
year={2018},
volume={E101-A},
number={11},
pages={1988-1992},
abstract={In this letter, we consider the harvested-energy fairness problem in cognitive multicast systems with simultaneous wireless information and power transfer. In the cognitive multicast system, a cognitive transmitter with multi-antenna sends the same information to cognitive users in the presence of licensed users, and cognitive users can decode information and harvest energy with a power-splitting structure. The harvested-energy fairness problem is formulated and solved by using two proposed algorithms, which are based on semidefinite relaxation with majorization-minimization method, and sequential parametric convex approximation with feasible point pursuit technique, respectively. Finally, the performances of the proposed solutions and baseline schemes are verified by simulation results.},
keywords={},
doi={10.1587/transfun.E101.A.1988},
ISSN={1745-1337},
month={November},}
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TY - JOUR
TI - Simultaneous Wireless Information and Power Transfer Solutions for Energy-Harvesting Fairness in Cognitive Multicast Systems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1988
EP - 1992
AU - Pham-Viet TUAN
AU - Insoo KOO
PY - 2018
DO - 10.1587/transfun.E101.A.1988
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E101-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2018
AB - In this letter, we consider the harvested-energy fairness problem in cognitive multicast systems with simultaneous wireless information and power transfer. In the cognitive multicast system, a cognitive transmitter with multi-antenna sends the same information to cognitive users in the presence of licensed users, and cognitive users can decode information and harvest energy with a power-splitting structure. The harvested-energy fairness problem is formulated and solved by using two proposed algorithms, which are based on semidefinite relaxation with majorization-minimization method, and sequential parametric convex approximation with feasible point pursuit technique, respectively. Finally, the performances of the proposed solutions and baseline schemes are verified by simulation results.
ER -