| Citation: | XU Yongjun, JIANG Siqiao, ZHANG Haibo, WANG Zhengqiang, ZHOU Jihua. Robust Secure Resource Allocation Algorithm for Cognitive Backscatter Communication with Hardware Impairment[J]. Journal of Electronics & Information Technology, 2024, 46(2): 652-661. doi: 10.11999/JEIT230117 | 
 
	                | [1] | XU Yongjun, GUI Guan, GACANIN H, et al. A survey on resource allocation for 5G heterogeneous networks: Current research, future trends, and challenges[J]. IEEE Communications Surveys & Tutorials, 2021, 23(2): 668–695. doi:  10.1109/COMST.2021.3059896. | 
| [2] | XU Yongjun, GU Bowen, HU R Q, et al. Joint computation offloading and radio resource allocation in MEC-based wireless-powered backscatter communication networks[J]. IEEE Transactions on Vehicular Technology, 2021, 70(6): 6200–6205. doi:  10.1109/TVT.2021.3077094. | 
| [3] | 张晓茜, 徐勇军. 面向零功耗物联网的反向散射通信综述[J]. 通信学报, 2022, 43(11): 199–212. doi:  10.11959/j.issn.1000-436x.2022199. ZHANG Xiaoxi and XU Yongjun. Survey on backscatter communication for zero-power IoT[J]. Journal on Communications, 2022, 43(11): 199–212. doi:  10.11959/j.issn.1000-436x.2022199. | 
| [4] | 徐勇军, 杨浩克, 李国军, 等. 多标签无线供电反向散射通信网络能效优化算法[J]. 电子与信息学报, 2022, 44(10): 3492–3498. doi:  10.11999/JEIT210772. XU Yongjun, YANG Haoke, LI Guojun, et al. Energy-efficient optimization algorithm in multi-tag wireless-powered backscatter communication networks[J]. Journal of Electronics &Information Technology, 2022, 44(10): 3492–3498. doi:  10.11999/JEIT210772. | 
| [5] | 徐勇军. 下垫式认知无线电网络动态资源分配问题研究[D]. [博士论文]. 吉林大学, 2015. XU Yongjun. Research on dynamic resource allocation for underlay cognitive radio networks[D]. [Ph. D. dissertation]. Jilin University, 2015. | 
| [6] | LI Xingwang, ZHENG Yike, KHAN W U, et al. Physical layer security of cognitive ambient backscatter communications for green internet-of-things[J]. IEEE Transactions on Green Communications and Networking, 2021, 5(3): 1066–1076. doi:  10.1109/TGCN.2021.3062060. | 
| [7] | LI Xingwang, WANG Qunshu, ZENG Ming, et al. Physical-layer authentication for ambient backscatter-aided NOMA symbiotic systems[J]. IEEE Transactions on Communications, 2023, 71(4): 2288–2303. doi:  10.1109/TCOMM.2023.3245659. | 
| [8] | XU Yongjun, XIE Hao, LI Dong, et al. Energy-efficient beamforming for heterogeneous industrial IoT networks with phase and distortion noises[J]. IEEE Transactions on Industrial Informatics, 2022, 18(11): 7423–7434. doi:  10.1109/TII.2022.3158612. | 
| [9] | LI Xingwang, LIU Huiling, LI Geng, et al. Effective capacity analysis of AmBC-NOMA communication systems[J]. IEEE Transactions on Vehicular Technology, 2022, 71(10): 11257–11261. doi:  10.1109/TVT.2022.3186871. | 
| [10] | JAFARI R and FAPOJUWO A O. Maximizing secondary users’ sum-throughput in an in-band full-duplex cognitive wireless powered backscatter communication network[J]. IEEE Systems Journal, 2022, 16(3): 4082–4093. doi:  10.1109/JSYST.2021.3124097. | 
| [11] | XIAO Sa, GUO Huayan, and LIANG Yingchang. Resource allocation for full-duplex-enabled cognitive backscatter networks[J]. IEEE Transactions on Wireless Communications, 2019, 18(6): 3222–3235. doi:  10.1109/TWC.2019.2912203. | 
| [12] | LYU Bin, GUO Haiyan, YANG Zhen, et al. Throughput maximization for hybrid backscatter assisted cognitive wireless powered radio networks[J]. IEEE Internet of Things Journal, 2018, 5(3): 2015–2024. doi:  10.1109/JIOT.2018.2820180. | 
| [13] | KANG Xin, LIANG Yingchang, and YANG Jing. Riding on the primary: A new spectrum sharing paradigm for wireless-powered IoT devices[J]. IEEE Transactions on Wireless Communications, 2018, 17(9): 6335–6347. doi:  10.1109/TWC.2018.2859389. | 
| [14] | ZHUANG Yuandong, LI Xi, JI Hong, et al. Optimal resource allocation for RF-powered underlay cognitive radio networks with ambient backscatter communication[J]. IEEE Transactions on Vehicular Technology, 2020, 69(12): 15216–15228. doi:  10.1109/TVT.2020.3037152. | 
| [15] | KISHORE R, GURUGOPINATH S, SOFOTASIOS P C, et al. Opportunistic ambient backscatter communication in RF-powered cognitive radio networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2019, 5(2): 413–426. doi:  10.1109/TCCN.2019.2907090. | 
| [16] | ZHANG Yu, GAO Feifei, FAN Lisheng, et al. Secure communications for multi-tag backscatter systems[J]. IEEE Wireless Communications Letters, 2019, 8(4): 1146–1149. doi:  10.1109/LWC.2019.2909199. | 
| [17] | WANG Pu, WANG Ning, DABAGHCHIAN M, et al. Optimal resource allocation for secure multi-user wireless powered backscatter communication with artificial noise[C]// IEEE Conference on Computer Communications, Paris, France, 2019: 460–468. | 
| [18] | XU Yongjun, GU Bowen, and LI Dong. Robust energy-efficient optimization for secure wireless-powered backscatter communications with a non-linear EH model[J]. IEEE Communications Letters, 2021, 25(10): 3209–3213. doi:  10.1109/LCOMM.2021.3097737. | 
| [19] | XU Yongjun, XIE Hao, WU Qingqing, et al. Robust max-min energy efficiency for RIS-aided HetNets with distortion noises[J]. IEEE Transactions on Communications, 2022, 70(2): 1457–1471. doi:  10.1109/TCOMM.2022.3141798. | 
| [20] | YE Yinghui, SHI Liqin, CHU Xiaoli, et al. Mutualistic cooperative ambient backscatter communications under hardware impairments[J]. IEEE Transactions on Communications, 2022, 70(11): 7656–7668. doi:  10.1109/TCOMM.2022.3201119. | 
| [21] | XU Yongjun, YANG Meng, YANG Yang, et al. Max-min energy-efficient optimization for cognitive heterogeneous networks with spectrum sensing errors and channel uncertainties[J]. IEEE Wireless Communications Letters, 2022, 11(6): 1113–1117. doi:  10.1109/LWC.2021.3130632. | 
