Secrecy Rate Maximization for Reconfigurable Intelligent Surface Aided Millimeter Wave System With Low-Resolution DACs
In this letter, we investigate the secrecy rate of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) system with low-resolution digital-to-analog converters (LDACs). Compared to the RIS-aided systems in most existing works, we consider how to alleviate the hardware loss and i...
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| Vydáno v: | IEEE communications letters Ročník 25; číslo 7; s. 2166 - 2170 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
IEEE
01.07.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1089-7798, 1558-2558 |
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| Abstract | In this letter, we investigate the secrecy rate of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) system with low-resolution digital-to-analog converters (LDACs). Compared to the RIS-aided systems in most existing works, we consider how to alleviate the hardware loss and improve the secrecy rate by using RIS. In particular, we formulate a secrecy rate maximization problem with hardware constraints. To handle the problem, an alternating optimization (AO)-based algorithm is proposed. Specifically, we first use the successive convex approximation (SCA) method to obtain the transmit beamforming. Then, the element-wise block coordinate descent (BCD) method is used to obtain the RIS phase shifts. Numerical results demonstrate that the RIS can mitigate the hardware loss, and the proposed AO-based algorithm with low complexity outperformances the baselines. |
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| AbstractList | In this letter, we investigate the secrecy rate of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) system with low-resolution digital-to-analog converters (LDACs). Compared to the RIS-aided systems in most existing works, we consider how to alleviate the hardware loss and improve the secrecy rate by using RIS. In particular, we formulate a secrecy rate maximization problem with hardware constraints. To handle the problem, an alternating optimization (AO)-based algorithm is proposed. Specifically, we first use the successive convex approximation (SCA) method to obtain the transmit beamforming. Then, the element-wise block coordinate descent (BCD) method is used to obtain the RIS phase shifts. Numerical results demonstrate that the RIS can mitigate the hardware loss, and the proposed AO-based algorithm with low complexity outperformances the baselines. |
| Author | Sun, Wei Zhao, Jun Xiu, Yue Zhang, Zhongpei |
| Author_xml | – sequence: 1 givenname: Yue orcidid: 0000-0002-8204-5389 surname: Xiu fullname: Xiu, Yue email: xiuyue@std.uestc.edu.cn organization: University of Electronic Science and Technology of China, Chengdu, China – sequence: 2 givenname: Jun orcidid: 0000-0002-3004-7091 surname: Zhao fullname: Zhao, Jun email: junzhao@ntu.edu.sg organization: Nanyang Technological University, Singapore – sequence: 3 givenname: Wei orcidid: 0000-0001-5648-5607 surname: Sun fullname: Sun, Wei email: weisun@stumail.neu.edu.cn organization: School of Computer Science and Engineering, Northeastern University, Shenyang, China – sequence: 4 givenname: Zhongpei orcidid: 0000-0003-2772-9937 surname: Zhang fullname: Zhang, Zhongpei email: zhangzp@uestc.edu.cn organization: University of Electronic Science and Technology of China, Chengdu, China |
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| Cites_doi | 10.1109/LWC.2020.2990431 10.1109/ITA.2015.7308988 10.1109/TWC.2020.3034895 10.1109/TWC.2018.2890607 10.1109/TWC.2019.2936025 10.1109/TWC.2017.2661749 10.1109/JSAC.2017.2687278 10.1109/LWC.2020.2980225 10.1017/CBO9780511804441 10.1109/LCOMM.2019.2924214 10.1109/ACCESS.2019.2924034 10.1109/JSAC.2020.3007211 10.1109/MCOM.001.1900107 10.1109/JSAC.2020.3000802 10.1109/TCOMM.2020.3001125 10.1109/GLOCOM.2018.8647620 10.1109/LWC.2020.3000490 |
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| References | ref13 karasik (ref7) 2019 ref23 ref15 zhi (ref14) 2020 ref20 ref11 liu (ref22) 2020 ref10 ref21 ref2 ref1 ref17 ref16 ref19 bishnoi (ref5) 2020 ref18 ref9 ref4 ref3 ref6 xiu (ref8) 2020 lu (ref12) 2020 |
| References_xml | – year: 2020 ident: ref12 article-title: Robust and secure beamforming for intelligent reflecting surface aided mmWave MISO systems publication-title: arXiv 2003 11195 – year: 2020 ident: ref5 article-title: Scalable Gaussian processes for predicting the properties of inorganic glasses with large datasets publication-title: arXiv 2007 02795 – year: 2019 ident: ref7 article-title: Beyond max-SNR: Joint encoding for reconfigurable intelligent surfaces publication-title: arXiv 1911 09443 – ident: ref2 doi: 10.1109/LWC.2020.2990431 – ident: ref16 doi: 10.1109/ITA.2015.7308988 – ident: ref23 doi: 10.1109/TWC.2020.3034895 – ident: ref20 doi: 10.1109/TWC.2018.2890607 – ident: ref3 doi: 10.1109/TWC.2019.2936025 – ident: ref15 doi: 10.1109/TWC.2017.2661749 – ident: ref13 doi: 10.1109/JSAC.2017.2687278 – ident: ref9 doi: 10.1109/LWC.2020.2980225 – ident: ref17 doi: 10.1017/CBO9780511804441 – ident: ref10 doi: 10.1109/LCOMM.2019.2924214 – ident: ref11 doi: 10.1109/ACCESS.2019.2924034 – year: 2020 ident: ref8 article-title: IRS-assisted millimeter wave communications: Joint power allocation and beamforming design publication-title: arXiv 2001 07467 – ident: ref1 doi: 10.1109/JSAC.2020.3007211 – ident: ref4 doi: 10.1109/MCOM.001.1900107 – year: 2020 ident: ref22 article-title: Deep residual learning for channel estimation in intelligent reflecting surface-assisted multi-user communications publication-title: arXiv 2009 01423 – year: 2020 ident: ref14 article-title: Uplink achievable rate of intelligent reflecting surface-aided millimeter-wave communications with low-resolution ADC and phase noise publication-title: arXiv 2008 00437 – ident: ref18 doi: 10.1109/JSAC.2020.3000802 – ident: ref6 doi: 10.1109/TCOMM.2020.3001125 – ident: ref21 doi: 10.1109/GLOCOM.2018.8647620 – ident: ref19 doi: 10.1109/LWC.2020.3000490 |
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| SubjectTerms | Algorithms alternating optimization algorithm Approximation Array signal processing Beamforming Complexity theory Digital to analog conversion Digital to analog converters Hardware low-resolution digital-to-analog converter Mathematical analysis Maximization Millimeter waves millimeter-wave Optimization Quantization (signal) Radio frequency Reconfigurable intelligent surface Reconfigurable intelligent surfaces Security |
| Title | Secrecy Rate Maximization for Reconfigurable Intelligent Surface Aided Millimeter Wave System With Low-Resolution DACs |
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