The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 인지 사용자가 전력 분할(PS)을 채택하는 SWIPT(동시 무선 정보 및 전력 전송) 기능을 갖춘 AN(인공 잡음) 지원 MISO(다중 입력 단일 출력) 인지 무선 네트워크를 고려합니다. 정보를 디코딩하고 에너지를 수확하는 수신기 아키텍처. 보안 통신을 지원하고 에너지 수확을 촉진하기 위해 AN은 CBS(인지 기지국)에서 정보 신호와 함께 전송됩니다. 비밀에너지 효율(SEE) 최대화 문제는 비밀율과 하베스트 에너지 요구사항, 일차 사용자의 간섭 요구사항의 제약으로 공식화됩니다. 그러나 이 어려운 문제는 분수 목적 함수와 최적화 변수 간의 결합으로 인해 볼록하지 않습니다. 어려운 문제를 해결하기 위해 이중 계층 반복 최적화 알고리즘이 개발되었습니다. 특히, 외부 레이어는 새로 도입된 엄격한 완화 변수에 대한 1차원 검색 알고리즘을 호출하는 반면, 내부 레이어는 Dinkelbach 방법을 활용하여 부분 최적화 문제를 보다 다루기 쉽게 만듭니다. 또한, 정보 신호 및 AN의 전력에 대한 닫힌 형식의 표현이 얻어집니다. 제안된 알고리즘의 효율성과 SEE 성능 향상에 있어 AN의 장점을 입증하기 위해 수치 시뮬레이션을 수행했습니다.
Ke WANG
Southeast University
Wei HENG
Southeast University
Xiang LI
Southeast University
Jing WU
Southeast University
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부
Ke WANG, Wei HENG, Xiang LI, Jing WU, "Energy-Efficient Secure Transmission for Cognitive Radio Networks with SWIPT" in IEICE TRANSACTIONS on Communications,
vol. E103-B, no. 9, pp. 1002-1010, September 2020, doi: 10.1587/transcom.2019EBP3180.
Abstract: In this paper, the artificial noise (AN)-aided multiple-input single-output (MISO) cognitive radio network with simultaneous wireless information and power transfer (SWIPT) is considered, in which the cognitive user adopts the power-splitting (PS) receiver architecture to simultaneously decode information and harvest energy. To support secure communication and facilitate energy harvesting, AN is transmitted with information signal at cognitive base station (CBS). The secrecy energy efficiency (SEE) maximization problem is formulated with the constraints of secrecy rate and harvested energy requirements as well as primary user's interference requirements. However, this challenging problem is non-convex due to the fractional objective function and the coupling between the optimization variables. For tackling the challenging problem, a double-layer iterative optimization algorithm is developed. Specifically, the outer layer invokes a one-dimension search algorithm for the newly introduced tight relaxation variable, while the inner one leverages the Dinkelbach method to make the fractional optimization problem more tractable. Furthermore, closed-form expressions for the power of information signal and AN are obtained. Numerical simulations are conducted to demonstrate the efficiency of our proposed algorithm and the advantages of AN in enhancing the SEE performance.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2019EBP3180/_p
부
@ARTICLE{e103-b_9_1002,
author={Ke WANG, Wei HENG, Xiang LI, Jing WU, },
journal={IEICE TRANSACTIONS on Communications},
title={Energy-Efficient Secure Transmission for Cognitive Radio Networks with SWIPT},
year={2020},
volume={E103-B},
number={9},
pages={1002-1010},
abstract={In this paper, the artificial noise (AN)-aided multiple-input single-output (MISO) cognitive radio network with simultaneous wireless information and power transfer (SWIPT) is considered, in which the cognitive user adopts the power-splitting (PS) receiver architecture to simultaneously decode information and harvest energy. To support secure communication and facilitate energy harvesting, AN is transmitted with information signal at cognitive base station (CBS). The secrecy energy efficiency (SEE) maximization problem is formulated with the constraints of secrecy rate and harvested energy requirements as well as primary user's interference requirements. However, this challenging problem is non-convex due to the fractional objective function and the coupling between the optimization variables. For tackling the challenging problem, a double-layer iterative optimization algorithm is developed. Specifically, the outer layer invokes a one-dimension search algorithm for the newly introduced tight relaxation variable, while the inner one leverages the Dinkelbach method to make the fractional optimization problem more tractable. Furthermore, closed-form expressions for the power of information signal and AN are obtained. Numerical simulations are conducted to demonstrate the efficiency of our proposed algorithm and the advantages of AN in enhancing the SEE performance.},
keywords={},
doi={10.1587/transcom.2019EBP3180},
ISSN={1745-1345},
month={September},}
부
TY - JOUR
TI - Energy-Efficient Secure Transmission for Cognitive Radio Networks with SWIPT
T2 - IEICE TRANSACTIONS on Communications
SP - 1002
EP - 1010
AU - Ke WANG
AU - Wei HENG
AU - Xiang LI
AU - Jing WU
PY - 2020
DO - 10.1587/transcom.2019EBP3180
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E103-B
IS - 9
JA - IEICE TRANSACTIONS on Communications
Y1 - September 2020
AB - In this paper, the artificial noise (AN)-aided multiple-input single-output (MISO) cognitive radio network with simultaneous wireless information and power transfer (SWIPT) is considered, in which the cognitive user adopts the power-splitting (PS) receiver architecture to simultaneously decode information and harvest energy. To support secure communication and facilitate energy harvesting, AN is transmitted with information signal at cognitive base station (CBS). The secrecy energy efficiency (SEE) maximization problem is formulated with the constraints of secrecy rate and harvested energy requirements as well as primary user's interference requirements. However, this challenging problem is non-convex due to the fractional objective function and the coupling between the optimization variables. For tackling the challenging problem, a double-layer iterative optimization algorithm is developed. Specifically, the outer layer invokes a one-dimension search algorithm for the newly introduced tight relaxation variable, while the inner one leverages the Dinkelbach method to make the fractional optimization problem more tractable. Furthermore, closed-form expressions for the power of information signal and AN are obtained. Numerical simulations are conducted to demonstrate the efficiency of our proposed algorithm and the advantages of AN in enhancing the SEE performance.
ER -